Neuroscience
1. Detecting cells using non-negative matrix factorization on calcium imaging data
Pages: 11-19
Author(s): Ryuichi Maruyama, Kazuma Maeda, Hajime Moroda, Ichiro Kato, Masashi Inoue, Hiroyoshi Miyakawa, Toru Aonishi
Learning Systems
2. Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning
Pages: 30-41
Author(s): Xiong Yang, Derong Liu, Ding Wang, Qinglai Wei
3. Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality
Pages: 59-71
Author(s): Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
4. A general soft label based Linear Discriminant Analysis for semi-supervised dimensionality reduction
Pages: 83-97
Author(s): Mingbo Zhao, Zhao Zhang, Tommy W.S. Chow, Bing Li
Mathematical and Computational Analysis
5. Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control
Pages: 1-10
Author(s): Guodong Zhang, Yi Shen
6. A collective neurodynamic optimization approach to bound-constrained nonconvex optimization
Pages: 20-29
Author(s): Zheng Yan, Jun Wang, Guocheng Li
7. Stability analysis of fractional-order Hopfield neural networks with time delays
Pages: 98-109
Author(s): Hu Wang, Yongguang Yu, Guoguang Wen
Engineering and Applications
8. Towards limb position invariant myoelectric pattern recognition using time-dependent spectral features
Pages: 42-58
Author(s): Rami N. Khushaba, Maen Takruri, Jaime Valls Miro, Sarath Kodagoda
9. Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition
Pages: 72-82
Author(s): Gonzalo Carvajal, Miguel Figueroa
Tuesday, May 27, 2014
Neural Networks, Volume 55, Pages 1-110, July 2014
Monday, May 26, 2014
Neural networks new articles 19-25 May, 2014
1. Comparing fixed and variable-width gaussian networks
Author(s): Věra Kůrková, Paul C. Kainen
Wednesday, May 21, 2014
IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 6, June 2014
1. A Self-Building and Cluster-Based Cognitive Fault Diagnosis System for Sensor Networks
Author(s): Alippi, C. ; Roveri, M. ; Trova, F.
Pages: 1021-1032
2. A Simple Scheme for Formation Control Based on Weighted Behavior Learning
Author(s): Lin, J. ; Hwang, K. ; Wang, Y.
Pages: 1033-1044
3. New Criteria for Global Robust Stability of Delayed Neural Networks With Norm-Bounded Uncertainties
Author(s): Arik, S.
Pages: 1045-1052
4. A Nonlinear Semantic-Preserving Projection Approach to Visualize Multivariate Periodical Time Series
Author(s): Blanchart, P. ; Depecker, M.
Pages: 1053-1070
5. Local Coordinate Concept Factorization for Image Representation
Author(s): Liu, H. ; Yang, Z. ; Yang, J. ; Wu, Z. ; Li, X.
Pages: 1071-1082
6. Global and Local Structure Preservation for Feature Selection
Author(s): Liu, X. ; Wang, L. ; Zhang, J. ; Yin, J. ; Liu, H.
Pages: 1083-1095
7. A Load-Balancing Self-Organizing Incremental Neural Network
Author(s): Zhang, H. ; Xiao, X. ; Hasegawa, O.
Pages: 1096-1105
8. Optimal Switching and Control of Nonlinear Switching Systems Using Approximate Dynamic Programming
Author(s): Heydari, A. ; Balakrishnan, S.N.
Pages: 1106-1117
9. Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM
Author(s): Laporte, L. ; Flamary, R. ; Canu, S. ; Dejean, S. ; Mothe, J.
Pages: 1118-1130
10. Multiset Canonical Correlations Using Globality Preserving Projections With Applications to Feature Extraction and Recognition
Author(s): Yuan, Y. ; Sun, Q.
Pages: 1131-1146
11. Efficient Exploratory Learning of Inverse Kinematics on a Bionic Elephant Trunk
Author(s): Rolf, M. ; Steil, J.J.
Pages: 1147-1160
12. Novel LMI-Based Condition on Global Asymptotic Stability for a Class of Cohen–Grossberg BAM Networks With Extended Activation Functions
Author(s): Zhang, Z. ; Cao, J. ; Zhou, D.
Pages: 1161-1172
13. Semisupervised Classification Through the Bag-of-Paths Group Betweenness
Author(s): Lebichot, B. ; Kivimaki, I. ; Francoisse, K. ; Saerens, M.
Pages: 1173-1186
14. Rapid Oscillation Fault Detection and Isolation for Distributed Systems via Deterministic Learning
Author(s): Chen, T. ; Wang, C. ; Hill, D.J.
Pages: 1187-1199
15. Gaussian Classifier-Based Evolutionary Strategy for Multimodal Optimization
Author(s): Dong, W. ; Zhou, M.
Pages: 1200-1216
16. Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
Author(s): Chen, C.L.P. ; Wen, G. ; Liu, Y. ; Wang, F.
Pages: 1217-1127
Author(s): Alippi, C. ; Roveri, M. ; Trova, F.
Pages: 1021-1032
2. A Simple Scheme for Formation Control Based on Weighted Behavior Learning
Author(s): Lin, J. ; Hwang, K. ; Wang, Y.
Pages: 1033-1044
3. New Criteria for Global Robust Stability of Delayed Neural Networks With Norm-Bounded Uncertainties
Author(s): Arik, S.
Pages: 1045-1052
4. A Nonlinear Semantic-Preserving Projection Approach to Visualize Multivariate Periodical Time Series
Author(s): Blanchart, P. ; Depecker, M.
Pages: 1053-1070
5. Local Coordinate Concept Factorization for Image Representation
Author(s): Liu, H. ; Yang, Z. ; Yang, J. ; Wu, Z. ; Li, X.
Pages: 1071-1082
6. Global and Local Structure Preservation for Feature Selection
Author(s): Liu, X. ; Wang, L. ; Zhang, J. ; Yin, J. ; Liu, H.
Pages: 1083-1095
7. A Load-Balancing Self-Organizing Incremental Neural Network
Author(s): Zhang, H. ; Xiao, X. ; Hasegawa, O.
Pages: 1096-1105
8. Optimal Switching and Control of Nonlinear Switching Systems Using Approximate Dynamic Programming
Author(s): Heydari, A. ; Balakrishnan, S.N.
Pages: 1106-1117
9. Nonconvex Regularizations for Feature Selection in Ranking With Sparse SVM
Author(s): Laporte, L. ; Flamary, R. ; Canu, S. ; Dejean, S. ; Mothe, J.
Pages: 1118-1130
10. Multiset Canonical Correlations Using Globality Preserving Projections With Applications to Feature Extraction and Recognition
Author(s): Yuan, Y. ; Sun, Q.
Pages: 1131-1146
11. Efficient Exploratory Learning of Inverse Kinematics on a Bionic Elephant Trunk
Author(s): Rolf, M. ; Steil, J.J.
Pages: 1147-1160
12. Novel LMI-Based Condition on Global Asymptotic Stability for a Class of Cohen–Grossberg BAM Networks With Extended Activation Functions
Author(s): Zhang, Z. ; Cao, J. ; Zhou, D.
Pages: 1161-1172
13. Semisupervised Classification Through the Bag-of-Paths Group Betweenness
Author(s): Lebichot, B. ; Kivimaki, I. ; Francoisse, K. ; Saerens, M.
Pages: 1173-1186
14. Rapid Oscillation Fault Detection and Isolation for Distributed Systems via Deterministic Learning
Author(s): Chen, T. ; Wang, C. ; Hill, D.J.
Pages: 1187-1199
15. Gaussian Classifier-Based Evolutionary Strategy for Multimodal Optimization
Author(s): Dong, W. ; Zhou, M.
Pages: 1200-1216
16. Adaptive Consensus Control for a Class of Nonlinear Multiagent Time-Delay Systems Using Neural Networks
Author(s): Chen, C.L.P. ; Wen, G. ; Liu, Y. ; Wang, F.
Pages: 1217-1127
Labels:
IEEE TNNLS,
journals
Tuesday, May 20, 2014
Paper submission deadline: IJCNN 2015
The paper submission deadline for the International Joint Conference on Neural Networks (IJCNN) 2015 is January 15, 2015. This conference will be held in Killarney, Ireland, July 12-17, 2015.
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IJCNN
Monday, May 19, 2014
Neural Networks new articles 12-18 May, 2014
1. A wavelet-based method for extracting intermittent discontinuities observed in human motor behavior
Author(s): Yasuyuki Inoue, Yutaka Sakaguchi
2. Immediate return preference emerged from a synaptic learning rule for return maximization
Author(s): Yoshiya Yamaguchi, Takeshi Aihara, Yutaka Sakai
3. Periodicity and dissipativity for memristor-based mixed time-varying delayed neural networks via differential inclusions
Author(s): Lian Duan, Lihong Huang
4. Discrete particle swarm optimization for identifying community structures in signed social networks
Author(s): Qing Cai, Maoguo Gong, Bo Shen, Lijia Ma, Licheng Jiao
5. Noise model based image -support vector regression with its application to short-term wind speed forecasting
Author(s): Qinghua Hu, Shiguang Zhang, Zongxia Xie, Jusheng Mi, Jie Wan
6. Grid topologies for the self-organizing map
Author(s): Ezequiel López-Rubio, Antonio Díaz Ramos
Author(s): Yasuyuki Inoue, Yutaka Sakaguchi
2. Immediate return preference emerged from a synaptic learning rule for return maximization
Author(s): Yoshiya Yamaguchi, Takeshi Aihara, Yutaka Sakai
3. Periodicity and dissipativity for memristor-based mixed time-varying delayed neural networks via differential inclusions
Author(s): Lian Duan, Lihong Huang
4. Discrete particle swarm optimization for identifying community structures in signed social networks
Author(s): Qing Cai, Maoguo Gong, Bo Shen, Lijia Ma, Licheng Jiao
5. Noise model based image -support vector regression with its application to short-term wind speed forecasting
Author(s): Qinghua Hu, Shiguang Zhang, Zongxia Xie, Jusheng Mi, Jie Wan
6. Grid topologies for the self-organizing map
Author(s): Ezequiel López-Rubio, Antonio Díaz Ramos
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journals,
neural networks
Friday, May 16, 2014
Reminder: paper submission deadline for IEEE CISDA 2014
A reminder that the deadline for submitting papers to the Seventh IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA) 2014 is June 15, 2014. This conference will be held in Hanoi, Vietnam, 14-17 December, 2014.
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conferences,
reminder
Thursday, May 15, 2014
Reminder: paper submission deadline for IEEE SSCI 2014
A reminder that the deadline for submitting papers to the IEEE Symposium Series on Computational Intelligence (SSCI) 2014 is 15 June 2014. This group of symposia will be held in Orlando, Florida, 9-12 December, 2014.
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call for papers,
conferences,
reminder
Wednesday, May 14, 2014
Reminder: conference paper deadline for ICAPR 2015
A reminder that the deadline for submitting papers to the Eighth International Conference on Advances in Pattern Recognition (ICAPR) 2015 is June 15, 2014. This conference will be held in Kolkata, India, January 4-7 2015.
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conferences,
reminder
Monday, May 12, 2014
Neural Networks new articles 5 - 11 May, 2014
1. Incorporating conditional random fields and active learning to improve sentiment identification
Author(s): Kunpeng Zhang, Yusheng Xie, Yi Yang, Aaron Sun, Hengchang Liu, Alok Choudhary
Author(s): Kunpeng Zhang, Yusheng Xie, Yi Yang, Aaron Sun, Hengchang Liu, Alok Choudhary
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journals,
neural networks
Wednesday, May 7, 2014
Neural Networks new articles 29 April - 5 May
1. Ideal regularization for learning kernels from labels
Author(s): Binbin Pan, Jianhuang Lai, Lixin Shen
2. Synaptic dynamics: Linear model and adaptation algorithm
Author(s): Ali Yousefi, Alireza A. Dibazar, Theodore W. Berger
Author(s): Binbin Pan, Jianhuang Lai, Lixin Shen
2. Synaptic dynamics: Linear model and adaptation algorithm
Author(s): Ali Yousefi, Alireza A. Dibazar, Theodore W. Berger
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journals,
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Monday, May 5, 2014
Call for Papers: IEEE SSCI 2014
Welcome to the sunshine of Orlando, Florida for the IEEE SSCI 2014, a
flagship international conference sponsored by the IEEE Computational
Intelligence Society (CIS) promoting all aspects of Computational
Intelligence (CI). The IEEE SSCI 2014 co-locates multiple exciting
symposiums at one single location, providing a unique opportunity to
encourage cross-fertilization and collaborations in all areas of CI. The
IEEE SSCI 2014 features a large number of keynotes, tutorials, and
special sessions. The IEEE SSCI 2014 will also offer a number of travel
grants as well as an exciting Doctoral Consortium.
We hope you could participate this exciting event, and look forward to seeing you in Orlando in December 2014!
Notification to authors: September 5, 2014
Final submission: October 5, 2014
Early registration: October 5, 2014
Website: www.ieee-ssci.org
For paper submissions, please go to the conference website: www.ieee-ssci.org and click the "Paper Submission" from the left panel, or directly go to the paper submission link at: ieee-cis.org/conferences/ ssci2014/upload.php
IEEE SSCI 2014 features the following Symposia:
General Chair: Haibo He, USA
General Program Chair: Cesare Alippi, Italy
We hope you could participate this exciting event, and look forward to seeing you in Orlando in December 2014!
Important dates
Paper submission: June 15, 2014Notification to authors: September 5, 2014
Final submission: October 5, 2014
Early registration: October 5, 2014
Website: www.ieee-ssci.org
For paper submissions, please go to the conference website: www.ieee-ssci.org and click the "Paper Submission" from the left panel, or directly go to the paper submission link at: ieee-cis.org/conferences/
IEEE SSCI 2014 features the following Symposia:
- ADPRL'14: IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, Huaguang Zhang, China, Jagannathan Sarangapani, USA, Lucian Busoniu, Romania.
- CCMB'14: IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain, Leonid Perlovsky, USA, Jose F Fontanari, Brazil, Angelo Cangelosi, UK, Daniel Levine, USA, Robert Kozma, USA
- CIASG'14: IEEE Symposium on Computational Intelligence Applications in Smart Grid, G. Kumar Venayagamoorthy, USA, Jung-Wook Park, Korea.
- CIBCI'14: IEEE Symposium on Computational Intelligence in Brain Computer Interfaces, Damien Coyle, UK, Robert Kozma, USA, Kai Keng Ang, Singapore.
- CIBD'14: IEEE Symposium on Computational Intelligence in Big Data, Yaochu Jin, UK, Yonghong Peng, UK, Nitesh Chawla, USA, Marios Polycarpou, Cyprus.
- CIBIM'14: IEEE Symposium on Computational Intelligence in Biometrics and Identity Management, Qinghan Xiao, Canada, David Zhang, China, Fabio Scotti, Italy
- CICA'14, IEEE Symposium on Computational Intelligence in Control and Automation, Xiao-Jun Zeng, UK.
- CICARE'14, IEEE Symposium on Computational Intelligence in healthcare and e-health, Amir Hussain, UK, Jonathan Wu, Canada.
- CIComms'14, IEEE Symposium on Computational Intelligence for Communication Systems and Networks, Sergey Andreev, Finland, Raymond Carroll, Ireland, Maode Ma, Singapore, Paolo Rocca, Italy.
- CICS'14, IEEE Symposium on Computational Intelligence in Cyber Security, Dipankar Dasgupta, USA
- CIDM'14, IEEE Symposium on Computational Intelligence and Data Mining, Zhi-Hua Zhou, China, Barbara Hammer, Germany, Carlotta Domeniconi, USA.
- CIDUE'14, IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, Yaochu Jin, UK, Robi Polikar, USA, Shengxiang Yang, UK
- CIEL'14, IEEE Symposium on Computational Intelligence in Ensemble Learning, Nikhil R. Pal, India, P. N. Suganthan, Singapore, Xin Yao, UK, Wenjia Wang, UK.
- CIES'14, IEEE Symposium on Computational Intelligence for Engineering Solutions, Michael Beer, UK, Rudolf Kruse, Germany, Vladik Kreinovich, USA.
- CIHLI'14, IEEE Symposium on Computational Intelligence for Human-like Intelligence, Jacek Mandziuk, Poland, Wlodzislaw Duch, Poland, Janusz A. Starzyk, USA.
- CIMSIVP'14, IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision Processing, Khan M Iftekharuddin, USA, Salim Bouzerdoum,Australia.
- CIPLS'14, IEEE Symposium on Computational Intelligence in Production and Logistics Systems, Bülent Çatay, Turkey, Raymond Chiong, Australia, Patrick Siarry, France.
- CIVTS'14, IEEE Symposium on Computational Intelligence in Vehicles and Transportation Systems, Dipti Srinivasan, Singapore, Justin Dauwels, Singapore, Ana Bazzan, Brazil
- EALS'14, IEEE Symposium on Evolving and Autonomous Learning Systems, Plamen Angelov, U.K., Dimitar Filev, USA, Nikola Kasabov, New Zealand.
- FOCI'14, IEEE Symposium on Foundations of Computational Intelligence, Manuel Ojeda-Aciego, Spain, Leonardo Franco, Spain, Carlos Cotta, Spain.
- IA'14, IEEE Symposium on Intelligent Agents, Hani Hagras, UK, Vincenzo Loia, Italy.
- IES'14, IEEE Symposium on Intelligent Embedded Systems, Cesare Alippi, Italy, Giacomo Boracchi, Italy, Manuel Roveri, Italy.
- ICES'14, IEEE International Conference on Evolvable Systems, Andrew Tyrrell, UK, Martin Trefzer, UK.
- ISIC'14, IEEE International Symposium on Independent Computing, Robert Kozma, USA, Qingfu Zhao, Japan, Cheng-Hsiung Hsieh, Taiwan, Neil Y. Yen, Japan.
- CIR2AT'14, IEEE Symposium on Computational Intelligence in Robotic Rehabilitation and Assistive Technologies, Gui DeSouza, USA, James Patton, USA, Georgios Kouroupetroglou, Greece
- MC'14, IEEE Workshop on Memetic Computing, Giovanni Iacca, Netherlands, Fabio Caraffini, UK, Ferrante Neri, UK
- MCDM'14, IEEE Symposium on Computational Intelligence in Multicriteria Decision-Making, Yaochu Jin, UK, Piero Bonissone, USA, Juergen Branke, UK
- RiiSS'14, IEEE Symposium on Robotic Intelligence in Informationally Structured Space, Janos Botzheim, Japan, Chu Kiong Loo, Malaysia.
- SDE'14, IEEE Symposium on Differential Evolution, Janez Brest, Slovenia, Swagatam Das, India, Ferrante Neri, UK
- SIS'14, IEEE Symposium on Swarm Intelligence, Yuhui Shi, China, P. N. Suganthan, Singapore.
General Chair: Haibo He, USA
General Program Chair: Cesare Alippi, Italy
Labels:
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Tuesday, April 29, 2014
Neural Networks new articles 21-27 April 2014
1. Relative entropy minimizing noisy non-linear neural network to approximate stochastic processes
Author(s): Mathieu N. Galtier, Camille Marini, Gilles Wainrib, Herbert Jaeger
Author(s): Mathieu N. Galtier, Camille Marini, Gilles Wainrib, Herbert Jaeger
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journals,
neural networks
Monday, April 28, 2014
Conference submission deadline: SEAL 2014
The deadline for submitting papers to the 10th International Conference on Simulated Evolution and Learning (SEAL) 2014 is 14 July, 2014. This conference will be held in Dunedin, New Zealand, 15-18 December, 2014.
Labels:
call for papers,
conferences
Friday, April 25, 2014
IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 5, May 2014
1. Classification in the Presence of Label Noise: A Survey
Author(s): Benoit Frenay and Michel Verleysen
Pages: 845 - 869
2. Efficient Algorithms for Exact Inference in Sequence Labeling SVMs
Author(s): Alexander Bauer; Nico Gornitz; Franziska Biegler; Klaus-Robert Muller; Marius Kloft
Pages: 870 - 881
3. Robust Adaptive Dynamic Programming and Feedback Stabilization of Nonlinear Systems
Author(s): Yu Jiang; Zhong-Ping Jiang
Pages: 882 - 893
4. A Spiking Self-Organizing Map Combining STDP, Oscillations, and Continuous Learning
Author(s): Timothy Rumbell; Susan L. Denham; Thomas Wennekers
Pages: 894 - 907
5. An Online Outlier Identification and Removal Scheme for Improving Fault Detection Performance
Author(s): Hasan Ferdowsi; Sarangapani Jagannathan; Maciej Zawodniok
Pages: 908 - 919
6. Fidelity-Based Probabilistic Q-Learning for Control of Quantum Systems
Author(s): Chunlin Chen; Daoyi Dong; Han-Xiong Li; Jian Chu; Tzyh-Jong Tarn
Pages: 920 - 933
7. On the Impact of Approximate Computation in an Analog DeSTIN Architecture
Author(s): Steven Young; Junjie Lu; Jeremy Holleman; Itamar Arel
Pages: 934 - 946
8. Adaptive Neural Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis
Author(s): Huanqing Wang; Bing Chen; Kefu Liu; Xiaoping Liu; Chong Lin
Pages: 947 - 958
9. Simplified Interval Type-2 Fuzzy Neural Networks
Author(s): Yang-Yin Lin; Shih-Hui Liao; Jyh-Yeong Chang; Chin-Teng Lin
Pages: 959 - 969
10. Modeling of Batch Processes Using Explicitly Time-Dependent Artificial Neural Networks
Author(s): Botla Ganesh; Vadlagattu Varun Kumar; Kalipatnapu Yamuna Rani
Pages: 970 - 979
11. Storing Sparse Messages in Networks of Neural Cliques
Author(s): Behrooz Kamary Aliabadi; Claude Berrou; Vincent Gripon; Xiaoran Jiang
Pages: 980 - 989
12. Incipient Interturn Fault Diagnosis in Induction Machines Using an Analytic Wavelet-Based Optimized Bayesian Inference
Author(s): Jeevanand Seshadrinath; Bhim Singh; Bijaya Ketan Panigrahi
Pages: 990 - 1001
13. A Scalable Stagewise Approach to Large-Margin Multiclass Loss-Based Boosting
Author(s): Sakrapee Paisitkriangkrai; Chunhua Shen; Anton van den Hengel
Pages: 1002 - 1013
14. Data-Driven MFAC for a Class of Discrete-Time Nonlinear Systems With RBFNN
Author(s): Yuanming Zhu; Zhongsheng Hou
Pages: 1013 - 1020
Author(s): Benoit Frenay and Michel Verleysen
Pages: 845 - 869
2. Efficient Algorithms for Exact Inference in Sequence Labeling SVMs
Author(s): Alexander Bauer; Nico Gornitz; Franziska Biegler; Klaus-Robert Muller; Marius Kloft
Pages: 870 - 881
3. Robust Adaptive Dynamic Programming and Feedback Stabilization of Nonlinear Systems
Author(s): Yu Jiang; Zhong-Ping Jiang
Pages: 882 - 893
4. A Spiking Self-Organizing Map Combining STDP, Oscillations, and Continuous Learning
Author(s): Timothy Rumbell; Susan L. Denham; Thomas Wennekers
Pages: 894 - 907
5. An Online Outlier Identification and Removal Scheme for Improving Fault Detection Performance
Author(s): Hasan Ferdowsi; Sarangapani Jagannathan; Maciej Zawodniok
Pages: 908 - 919
6. Fidelity-Based Probabilistic Q-Learning for Control of Quantum Systems
Author(s): Chunlin Chen; Daoyi Dong; Han-Xiong Li; Jian Chu; Tzyh-Jong Tarn
Pages: 920 - 933
7. On the Impact of Approximate Computation in an Analog DeSTIN Architecture
Author(s): Steven Young; Junjie Lu; Jeremy Holleman; Itamar Arel
Pages: 934 - 946
8. Adaptive Neural Tracking Control for a Class of Nonstrict-Feedback Stochastic Nonlinear Systems With Unknown Backlash-Like Hysteresis
Author(s): Huanqing Wang; Bing Chen; Kefu Liu; Xiaoping Liu; Chong Lin
Pages: 947 - 958
9. Simplified Interval Type-2 Fuzzy Neural Networks
Author(s): Yang-Yin Lin; Shih-Hui Liao; Jyh-Yeong Chang; Chin-Teng Lin
Pages: 959 - 969
10. Modeling of Batch Processes Using Explicitly Time-Dependent Artificial Neural Networks
Author(s): Botla Ganesh; Vadlagattu Varun Kumar; Kalipatnapu Yamuna Rani
Pages: 970 - 979
11. Storing Sparse Messages in Networks of Neural Cliques
Author(s): Behrooz Kamary Aliabadi; Claude Berrou; Vincent Gripon; Xiaoran Jiang
Pages: 980 - 989
12. Incipient Interturn Fault Diagnosis in Induction Machines Using an Analytic Wavelet-Based Optimized Bayesian Inference
Author(s): Jeevanand Seshadrinath; Bhim Singh; Bijaya Ketan Panigrahi
Pages: 990 - 1001
13. A Scalable Stagewise Approach to Large-Margin Multiclass Loss-Based Boosting
Author(s): Sakrapee Paisitkriangkrai; Chunhua Shen; Anton van den Hengel
Pages: 1002 - 1013
14. Data-Driven MFAC for a Class of Discrete-Time Nonlinear Systems With RBFNN
Author(s): Yuanming Zhu; Zhongsheng Hou
Pages: 1013 - 1020
Labels:
IEEE TNNLS,
journals,
neural networks
Thursday, April 24, 2014
Conference paper deadline: ICAPR 2015
The deadline for submitting papers to the Eighth International Conference on Advances in Pattern Recognition (ICAPR) 2015 is June 15, 2014. This conference will be held in Kolkata, India, January 4-7 2015.
Labels:
call for papers,
conferences
Wednesday, April 23, 2014
Neural Networks Volume 54, Pages 1-122, June 2014
Neural Networks Letters
1. Interaction of feedforward and feedback streams in visual cortex in a firing-rate model of columnar computationsAuthor(s): Tobias Brosch, Heiko Neumann
Pages: 11-16
Learning Systems
2. Learning invariant object recognition from temporal correlation in a hierarchical networkAuthor(s): Markus Lessmann, Rolf P. Würtz
Pages: 70-84
3. Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes
Author(s): Yuri Quintana-Pacheco, Daniel Ruiz-Fernández, Agustín Magrans-Rico
Pages: 95-102
Mathematical and Computational Analysis
4. An improved robust stability result for uncertain neural networks with multiple time delaysAuthor(s): Sabri Arik
Pages: 1-10
5. Solving the linear interval tolerance problem for weight initialization of neural networks
Author(s): S.P. Adam, D.A. Karras, G.D. Magoulas, M.N. Vrahatis
Pages: 17-37
6. Necessary and sufficient condition for multistability of neural networks evolving on a closed hypercube
Author(s): Mauro Di Marco, Mauro Forti, Massimo Grazzini, Luca Pancioni
Pages: 38-48
7. Stable locality sensitive discriminant analysis for image recognition
Author(s): Quanxue Gao, Jingjing Liu, Kai Cui, Hailin Zhang, Xiaogang Wang
Pages: 49-56
8. Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach
Author(s): Xian-Ming Zhang, Qing-Long Han
Pages: 57-69
9. Impulsive synchronization schemes of stochastic complex networks with switching topology: Average time approach
Author(s): Chaojie Li, Wenwu Yu, Tingwen Huang
Pages: 85-94
10. New criterion of asymptotic stability for delay systems with time-varying structures and delays
Author(s): Bo Liu, Wenlian Lu, Tianping Chen
Pages: 103-111
11. A systematic method for analyzing robust stability of interval neural networks with time-delays based on stability criteria
Author(s): Zhenyuan Guo, Jun Wang, Zheng Yan
Pages: 112-122
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journals,
neural networks
Tuesday, April 22, 2014
Neural Networks new articles 15 April - 21 April
1. Stability analysis of fractional-order Hopfield neural networks with time delays
Author(s): Hu Wang, Yongguang Yu, Guoguang Wen
2. A general soft label based linear discriminant analysis for semi-supervised dimensionality reduction
Author(s): Mingbo Zhao, Zhao Zhang, Tommy W.S. Chow, Bing Li
Author(s): Hu Wang, Yongguang Yu, Guoguang Wen
2. A general soft label based linear discriminant analysis for semi-supervised dimensionality reduction
Author(s): Mingbo Zhao, Zhao Zhang, Tommy W.S. Chow, Bing Li
Labels:
journals,
neural networks
Monday, April 21, 2014
Conference paper deadline: IEEE CISDA 2014
The deadline for submitting papers to the Seventh IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA) 2014 is June 15, 2014. This conference will be held in Hanoi, Vietnam, 14-17 December, 2014.
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Friday, April 18, 2014
Conference paper deadline: SCIS and ISIS 2014
The deadline for the jointly-held conferences Soft Computing and Intelligent Systems (SCIS) and International Symposium on Advanced Intelligent Systems (ISIS) 2014 is 30 June, 2014. This conference will be held in Kitakyushu, Japan, December 3-6, 2014.
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conferences
Thursday, April 17, 2014
Conference paper deadline: UKCI 2014
The deadline for submitting papers to the UK Workshop on Computational Intelligence (UKCI) 2014 is 19 May 2014. This conference will be held in Bradford, UK, 8-10 September, 2014.
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call for papers,
conferences
Wednesday, April 16, 2014
Call for Papers: Special Issue on Real-Time Strategy Games IEEE TCIAIG
Special issue editors: Michael Buro, Santiago Ontañón and Mike Preuss
In recent years game AI for real-time strategy (RTS) games has become an active research area. Producing AI players (bots) which are able to consistently beat even average human players (without cheating) in these games has risen as a real challenge. Thus, in RTS games, player satisfaction cannot simply be achieved by “downgrading” the AI, as is possible in man other game genres. In consequence, stronger AI players make the game more interesting.
Recent RTS AI (e.g. StarCraft) tournaments have stimulated the creation of new bots with new concepts and architectures and led to a greatly increased number of publications addressing some of the many open AI problems in RTS games. For example, RTS game aspects such as resource management, scouting, real-time strategic and tactical planning, and others, call for the application of innovative CI/AI methods. This special issue welcomes high-quality work in the area of real-time strategy games. Topics include but are not limited to:
Deadline for submissions: July 1, 2014 Final copy due: February 1, 2015
Notification of Acceptance: November 1, 2014 Publication: June 2015
In recent years game AI for real-time strategy (RTS) games has become an active research area. Producing AI players (bots) which are able to consistently beat even average human players (without cheating) in these games has risen as a real challenge. Thus, in RTS games, player satisfaction cannot simply be achieved by “downgrading” the AI, as is possible in man other game genres. In consequence, stronger AI players make the game more interesting.
Recent RTS AI (e.g. StarCraft) tournaments have stimulated the creation of new bots with new concepts and architectures and led to a greatly increased number of publications addressing some of the many open AI problems in RTS games. For example, RTS game aspects such as resource management, scouting, real-time strategic and tactical planning, and others, call for the application of innovative CI/AI methods. This special issue welcomes high-quality work in the area of real-time strategy games. Topics include but are not limited to:
- Adversarial real-time planning in RTS games
- Bot reactiveness: learning and adaptation in RTS bots
- Build order optimization and its relation to strategies and the metagame
- Scouting and uncertainty management in RTS games
- Path-finding and group movement
- Combat simulation and AI for micro-management
- Opponent modeling, especially strategy prediction
- Complexity measurements for RTS games
- Communication and cooperation with and within RTS bots
- New forms of interaction with the player
- AI adaptations for more satisfying play experience
- Difficulty adaptation, ability-based matching, ladders, and tournaments
- Automated level/unit/map design for RTS games
- Multiplayer online battle arena (MOBA) games: the next generation of real-time strategy?
Deadline for submissions: July 1, 2014 Final copy due: February 1, 2015
Notification of Acceptance: November 1, 2014 Publication: June 2015
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Tuesday, April 15, 2014
Reminder: paper submission deadline for KES 2014
A reminder that the deadline for submitting papers to the 18th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES) 2014 is 15 March, 2014. This conference will be held in Gdynia, Poland, 15-17 September, 2014.
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Monday, April 14, 2014
IEEE Computational Intelligence Magazine Volume 9 Issue 2 May 2014
1. What Is Your Main IEEE Society? [Editor's Remarks]
Author(s): Ishibuchi, H.
2. President's Greeting [President's Message]
Author(s): Yao, X.
3. CIS Society Officers
4. Newly Elected CIS Administrative Committee Members (2014-2016) [Society Briefs]
Author(s): Yao, X.
5. IEEE Fellows - Class of 2014 [Society Briefs]
Author(s): Bezdek, J.
6. A Report on the CIS Second Video Competition [Society Briefs]
Author(s): Matthews, S. ; Abdool, A. ; Eliades, D. ; Coyle, D. ; Posada, J. ; Martin, E. ; Sperduti, A. ; Alippi, C. ; Estevez, P.
7. CIS Publication Spotlight
Author(s): Liu, D. ; Lin, C. ; Greenwood, G. ; Lucas, S. ; Zhang, Z.
8. Special Issue on Computational Intelligence for Community-Centric Systems [Guest Editorial]
Author(s): Kubota, N. ; Liu, H.
9. Context-Aware Personal Information Retrieval From Multiple Social Networks
Author(s): Han, X. ; Wei, W. ; Miao, C. ; Mei, J. ; Song, H.
10. Landmark-Based Methods for Temporal Alignment of Human Motions
Author(s): de Dios, P. ; Chung, P. ; Meng, Q.
11. Muscle Fatigue Tracking with Evoked EMG via Recurrent Neural Network: Toward Personalized Neuroprosthetics
Author(s): Li, Z. ; Hayashibe, M. ; Fattal, C. ; Guiraud, D.
12. Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]
Author(s): Cambria, E. ; White, B.
13. A Memetic Algorithm for Resource Allocation Problem Based on Node-Weighted Graphs [Application Notes]
Author(s): Wu, J. ; Chang, Z. ; Yuan, L. ; Hou, Y. ; Gong, M.
14. Conference Calendar
Author(s): Haddow, P.
15. Call for Papers for Journal Special Issues
16. CEC 2015
Author(s): Ishibuchi, H.
2. President's Greeting [President's Message]
Author(s): Yao, X.
3. CIS Society Officers
4. Newly Elected CIS Administrative Committee Members (2014-2016) [Society Briefs]
Author(s): Yao, X.
5. IEEE Fellows - Class of 2014 [Society Briefs]
Author(s): Bezdek, J.
6. A Report on the CIS Second Video Competition [Society Briefs]
Author(s): Matthews, S. ; Abdool, A. ; Eliades, D. ; Coyle, D. ; Posada, J. ; Martin, E. ; Sperduti, A. ; Alippi, C. ; Estevez, P.
7. CIS Publication Spotlight
Author(s): Liu, D. ; Lin, C. ; Greenwood, G. ; Lucas, S. ; Zhang, Z.
8. Special Issue on Computational Intelligence for Community-Centric Systems [Guest Editorial]
Author(s): Kubota, N. ; Liu, H.
9. Context-Aware Personal Information Retrieval From Multiple Social Networks
Author(s): Han, X. ; Wei, W. ; Miao, C. ; Mei, J. ; Song, H.
10. Landmark-Based Methods for Temporal Alignment of Human Motions
Author(s): de Dios, P. ; Chung, P. ; Meng, Q.
11. Muscle Fatigue Tracking with Evoked EMG via Recurrent Neural Network: Toward Personalized Neuroprosthetics
Author(s): Li, Z. ; Hayashibe, M. ; Fattal, C. ; Guiraud, D.
12. Jumping NLP Curves: A Review of Natural Language Processing Research [Review Article]
Author(s): Cambria, E. ; White, B.
13. A Memetic Algorithm for Resource Allocation Problem Based on Node-Weighted Graphs [Application Notes]
Author(s): Wu, J. ; Chang, Z. ; Yuan, L. ; Hou, Y. ; Gong, M.
14. Conference Calendar
Author(s): Haddow, P.
15. Call for Papers for Journal Special Issues
16. CEC 2015
Tuesday, April 8, 2014
Neural Networks new articles 31 March - 6 April
1. Model, analysis, and evaluation of the effects of analog VLSI arithmetic on linear subspace-based image recognition
Author(s): Gonzalo Carvajal, Miguel Figueroa
Author(s): Gonzalo Carvajal, Miguel Figueroa
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journals,
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Monday, April 7, 2014
Call for Special Session Proposals for IEEE SSCI 2014
The IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2014) invites Special Session proposals for our December 9 - 12, 2014 conference in Orlando, Florida, USA. Special session proposals can be for any of the symposium under the IEEE SSCI 2014 umbrella. Special Session proposals should include the following:
The deadline for special session proposals is April 15, 2014.
- A brief description, rationale or motivation of the proposed session
- The title of the proposed special session, and the specific symposium under which the special session should be listed
- List of topics and the scope
- A list of authors who have already been invited to participate (if any)
- Short bio information of the SS organizers
The deadline for special session proposals is April 15, 2014.
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Thursday, April 3, 2014
IEEE TNLS Call for Papers: Special issue on "Neurodynamic Systems for Optimization and Applications"
Recurrent neural networks, as dynamical systems, are usually used as models for solving computationally intensive problems. Because of their inherent nature of parallel and distributed information processing, recurrent neural networks are promising computational models for real-time applications. Constrained optimization problems arise in a wide variety of scientific and engineering applications, including signal and image processing, system identification, robot control, process control, pattern recognition, etc. Since the Hopfield neural network was introduced for solving optimization problems, significant progress has been made in theory, algorithms and applications. A number of neurodynamic models have been proposed for solving different problems ranging from discrete optimization to continuous optimization, linear programming to nonlinear optimization, convex optimization to non-convex optimization, smooth optimization to non-smooth optimization, numerical software to analog hardware implementations, etc. Some of them have been successfully applied to robot control, process control, signal and image processing, pattern recognition and classification, economic prediction and so on. In addition, as a kind of neuromorphic systems, they are potentially useful for simulating the brain functions, which is an important topic in neuroscience.
The objective of this special issue is to bring together recent advances in the field of neurodynamic systems for solving optimization problems. We invite original and unpublished research contributions in all relevant areas. We will encourage submissions of papers with new models and applications which would further promote research activities in this area.
Topics of interest include, but are not limited to:
Dec. 31, 2014 – Notification to authors
Feb. 15, 2015 – Deadline for submission of revised manuscripts
Mar.1, 2015 – Final decision
May/June 2015 – Special issue publication in the IEEE TNNLS.
2. Submit the manuscript by Aug 15, 2014 at the IEEE-TNNLS webpage http://mc.manuscriptcentral.com/tnnls and follow the submission procedure. Please indicate clearly on the first page of the manuscript and the Author’s Cover Letter that the manuscript has been submitted to the Special Issue on Neurodynamic Systems for Optimization and Applications. Send also an e-mail to chenglong@compsys.ia.ac.cn with subject “TNNLS special issue submission” to notify the editors of your submission.
Huazhong University of Science and Technology, China
zgzeng@hust.edu.cn
http://auto.hust.edu.cn/zhigangzeng/
Andrzej Cichocki
Brain Science Institute, RIKEN, Japan
cia@braiin.riken.jp
http://www.bsp.brain.riken.jp/~cia/
Long Cheng
Institute of Automation, Chinese Academy of Sciences, China
long.cheng@ia.ac.cn
http://compsys.ia.ac.cn/~chenglong
Yousheng Xia
Fuzhou University, China
ysxia@fzu.edu.cn
http://cmcs.fzu.edu.cn/action-model-name-teacher-itemid-34
Xiaolin Hu
Tsinghua University, China
xlhu@tsinghua.edu.cn
www.xlhu.cn
The objective of this special issue is to bring together recent advances in the field of neurodynamic systems for solving optimization problems. We invite original and unpublished research contributions in all relevant areas. We will encourage submissions of papers with new models and applications which would further promote research activities in this area.
Topics of interest include, but are not limited to:
- Neurodynamic models for constrained optimization
- Neurodynamic models for multi-objective optimization
- Neurodynamic models for large-scale optimization problems
- Neurodynamic models for deep learning
- Neurodynamic models for optimal control
- Neurodynamic models for tensor decomposition
- Analysis of neurodynamic optimization systems
- Neurodynamic optimization in the brain
- Neurodynamic optimization for process control
- Neurodynamic optimization for robot control
- Neurodynamic optimization for biomedical engineering problems
- Neurodynamic optimization for signal processing
- Neurodynamic optimization for image processing
- Neurodynamic optimization for support vector machine learning
- Neurodynamic optimization for pattern recognition
- Neurodynamic optimization for other applications
IMPORTANT DATES
Aug. 15, 2014 – Deadline for manuscript submissionDec. 31, 2014 – Notification to authors
Feb. 15, 2015 – Deadline for submission of revised manuscripts
Mar.1, 2015 – Final decision
May/June 2015 – Special issue publication in the IEEE TNNLS.
SUBMISSION INSTRUCTIONS
1. Read the information for authors at http://cis.ieee.org/tnnls2. Submit the manuscript by Aug 15, 2014 at the IEEE-TNNLS webpage http://mc.manuscriptcentral.com/tnnls and follow the submission procedure. Please indicate clearly on the first page of the manuscript and the Author’s Cover Letter that the manuscript has been submitted to the Special Issue on Neurodynamic Systems for Optimization and Applications. Send also an e-mail to chenglong@compsys.ia.ac.cn with subject “TNNLS special issue submission” to notify the editors of your submission.
GUEST EDITORS
Zhigang ZengHuazhong University of Science and Technology, China
zgzeng@hust.edu.cn
http://auto.hust.edu.cn/zhigangzeng/
Andrzej Cichocki
Brain Science Institute, RIKEN, Japan
cia@braiin.riken.jp
http://www.bsp.brain.riken.jp/~cia/
Long Cheng
Institute of Automation, Chinese Academy of Sciences, China
long.cheng@ia.ac.cn
http://compsys.ia.ac.cn/~chenglong
Yousheng Xia
Fuzhou University, China
ysxia@fzu.edu.cn
http://cmcs.fzu.edu.cn/action-model-name-teacher-itemid-34
Xiaolin Hu
Tsinghua University, China
xlhu@tsinghua.edu.cn
www.xlhu.cn
Labels:
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Wednesday, April 2, 2014
Neural Networks Volume 53, pages 1-172, May 2014
Neural Networks Letters
1. Further results on robustness analysis of global exponential stability of recurrent neural networks with time delays and random disturbancesAuthor(s): Weiwei Luo, Kai Zhong, Song Zhu, Yi Shen
Pages: 127-133
2. Fastest strategy to achieve given number of neuronal firing in theta model
Author(s): Jiaoyan Wang, Qingyun Wang, Guanrong Chen
Pages: 134-145
3. Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays
Author(s): Jinde Cao, Ying Wan
Pages: 165-172
Learning Systems
4. Cross-person activity recognition using reduced kernel extreme learning machineAuthor(s): Wan-Yu Deng, Qing-Hua Zheng, Zhong-Min Wang
Pages: 1-7
5. Robust head pose estimation via supervised manifold learning
Author(s): Chao Wang, Xubo Song
Pages: 15-25
6. Assist-as-needed robotic trainer based on reinforcement learning and its application to dart-throwing
Author(s): Chihiro Obayashi, Tomoya Tamei, Tomohiro Shibata
Pages: 52-60
7. Kernel learning at the first level of inference
Author(s): Gavin C. Cawley, Nicola L.C. Talbot
Pages: 69-80
8. Similarity preserving low-rank representation for enhanced data representation and effective subspace learning
Author(s): Zhao Zhang, Shuicheng Yan, Mingbo Zhao
Pages: 81-94
9. Learning using privileged information: SVM+ and weighted SVM
Author(s): Maksim Lapin, Matthias Hein, Bernt Schiele
Pages: 95-108
10. Safe semi-supervised learning based on weighted likelihood
Author(s): Masanori Kawakita, Jun’ichi Takeuchi
Pages: 146-164
Mathematical and Computational Analysis
11. Synchronization control of memristor-based recurrent neural networks with perturbationsAuthor(s): Weiping Wang, Lixiang Li, Haipeng Peng, Jinghua Xiao, Yixian Yang
Pages: 8-14
12. Effects of asymmetric coupling and self-coupling on metastable dynamical transient rotating waves in a ring of sigmoidal neurons
Author(s): Yo Horikawa
Pages: 26-39
13. Generalization performance of Gaussian kernels SVMC based on Markov sampling
Author(s): Jie Xu, Yuan Yan Tang, Bin Zou, Zongben Xu, Luoqing Li, Yang Lu
Pages: 40-51
14. Convergence behavior of delayed discrete cellular neural network without periodic coefficients
Author(s): Jinling Wang, Haijun Jiang, Cheng Hu, Tianlong Ma
Pages: 61-68
15. Multiple image mu-stability of neural networks with unbounded time-varying delays
Author(s): Lili Wang, Tianping Chen
Pages: 109-118
16. Extreme learning machine for ranking: Generalization analysis and applications
Author(s): Hong Chen, Jiangtao Peng, Yicong Zhou, Luoqing Li, Zhibin Pan
Pages: 119-126
Labels:
journals,
neural networks
Tuesday, April 1, 2014
Neural Networks new articles 24-30 March
1. Toward limb position invariant myoelectric pattern recognition using time-dependent spectral features
Author(s): Rami N. Khushaba, Maen Takruri, Jaime Valls Miro, Sarath Kodagoda
2. A collective neurodynamic optimization approach to bound-constrained nonconvex optimization
Author(s): Zheng Yan, Jun Wang, Guocheng Li
3. Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control
Author(s): Guodong Zhang, Yi Shen
4. Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning
Author(s): Xiong Yang, Derong Liu, Ding Wang, Qinglai Wei
5. A global coupling index of multivariate neural series with application to the evaluation of mild cognitive impairment
Author(s): Dong Wen, Qing Xue, Chengbiao Lu, Xinyong Guan, Yuping Wang, Xiaoli Li
6. Detecting cells using non-negative matrix factorization on calcium imaging data
Author(s): Ryuichi Maruyama, Kazuma Maeda, Hajime Moroda, Ichiro Kato, Masashi Inoue, Hiroyoshi Miyakawa, Toru Aonishi
Author(s): Rami N. Khushaba, Maen Takruri, Jaime Valls Miro, Sarath Kodagoda
2. A collective neurodynamic optimization approach to bound-constrained nonconvex optimization
Author(s): Zheng Yan, Jun Wang, Guocheng Li
3. Exponential synchronization of delayed memristor-based chaotic neural networks via periodically intermittent control
Author(s): Guodong Zhang, Yi Shen
4. Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning
Author(s): Xiong Yang, Derong Liu, Ding Wang, Qinglai Wei
5. A global coupling index of multivariate neural series with application to the evaluation of mild cognitive impairment
Author(s): Dong Wen, Qing Xue, Chengbiao Lu, Xinyong Guan, Yuping Wang, Xiaoli Li
6. Detecting cells using non-negative matrix factorization on calcium imaging data
Author(s): Ryuichi Maruyama, Kazuma Maeda, Hajime Moroda, Ichiro Kato, Masashi Inoue, Hiroyoshi Miyakawa, Toru Aonishi
Labels:
journals,
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Monday, March 31, 2014
IEEE Transactions on Evolutionary Computation Volume 18, Number 2, April 2014
PAPERS
1. Artificial Biochemical Networks: Evolving Dynamical Systems to Control Dynamical SystemsAuthor(s): M. A. Lones, L. A. Fuente, A. P. Turner, L. S. D. Caves, S. Stepney, S. L. Smith, and A. M. Tyrrell
Pages: 145-166
2. Multi-Objective Optimization by Using Evolutionary Algorithms: The p-Optimality Criteria
Author(s): E. Carre ̃no Jara
Pages: 167-179
3. A Gaussian Process Surrogate Model Assisted Evolutionary Algorithm for Medium Scale Expensive Optimization Problems
Author(s): B. Liu, Q. Zhang, and G. G. E. Gielen
Pages: 180-192
4. Automatic Design of Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling via Cooperative Coevolution Genetic Programming
Author(s): S. Nguyen, M. Zhang, M. Johnston, and K. Chen Tan
Pages: 193-208
5. An Improved Differential Evolution Algorithm for Practical Dynamic Scheduling in Steelmaking-Continuous Casting Production
Author(s): L. Tang, Y. Zhao, and J. Liu
Pages: 209-225
6. Frequency Fitness Assignment
Author(s): T. Weise, M. Wan, P. Wang, K. Tang, A. Devert, and X. Yao
Pages: 226-243
7. Localization of License Plate Number Using Dynamic Image Processing Techniques and Genetic Algorithms
Author(s): G. Abo Samra and F. Khalefah
Pages: 244-257
8. Comparison Study of Swarm Intelligence Techniques for the Annual Crop Planning Problem
Author(s): S. Chetty and A. O. Adewumi
Pages: 258-268
9. Fuzzy-Based Pareto Optimality for Many-Objective Evolutionary Algorithms
Author(s): Z. He, G. G. Yen, and J. Zhang
Pages: 269-287
10. A Distance-Based Ranking Model Estimation of Distribution Algorithm for the Flowshop Scheduling Problem
Author(s): J. Ceberio, E. Irurozki, A. Mendiburu, and J. A. Lozano
Pages: 286-300
LETTER
11. A Discrete Firefly Algorithm for the Multi-Objective Hybrid Flowshop Scheduling ProblemsAuthor(s): M. K. Marichelvam, T. Prabaharan, and X. S. Yang
Pages: 301
Friday, March 28, 2014
IEEE Transactions on Fuzzy Systems Volume 22, Number 2, April 2014
REGULAR PAPERS
1. Fuzzy Approximation-Based Adaptive Control of Nonlinear Delayed Systems With Unknown Dead ZoneAuthor(s): B.Chen,X.Liu,K.Liu,and C.Lin
Pages: 237-248
2. Output Feedback Predictive Control With One Free Control Move for Nonlinear Systems Represented by a Takagi–Sugeno Model
Author(s): B.Ding and X.Ping
Pages: 249-263
3. Individual Decision Making Can Drive Epidemics: A Fuzzy Cognitive Map Study
Author(s): S. Mei, Y. Zhu, X. Qiu, X. Zhou, Z. Zu, A. V. Boukhanovsky, and P. M. A. Sloot
Pages: 264-273
4. Adaptive Fault Diagnosis for T–S Fuzzy Systems With Sensor Faults and System Performance Analysis
Author(s): Q.Shen, B.Jiang, and P.Shi
Pages: 274-285
5. Adaptive Fuzzy Hierarchical Sliding-Mode Control for the Trajectory Tracking of Uncertain Underactuated Nonlinear Dynamic Systems
Author(s): C.-L.Hwang, C.-C.Chiang, and Y.-W.Yeh
Pages: 286-299
6. Atanassov’s Intuitionistic Fuzzy Programming Method for Heterogeneous Multiattribute Group Decision Making With Atanassov’s Intuitionistic Fuzzy Truth Degrees
Author(s): S.-P. Wan and D.-F. Li
Pages: 300-312
7. Novel Stability Criteria for T–S Fuzzy Systems
Author(s): X. Zhao, L. Zhang, P. Shi, and H. R. Karimi
Pages: 313-323
8. A Fuzzy Model With Online Incremental SVM and Margin-Selective Gradient Descent Learning for Classification Problems
Author(s): W.-Y. Cheng and C.-F. Juang
Pages: 324-337
9. Adaptive Fuzzy Observer-Based Active Fault-Tolerant Dynamic Surface Control for a Class of Nonlinear Systems With Actuator Faults
Author(s): Q.Shen, B.Jiang, and V.Cocquempot
Pages: 338-349
10. Universal Fuzzy Integral Sliding-Mode Controllers Based on T–S Fuzzy Models
Author(s): Q. Gao, L. Liu, G. Feng, Y. Wang, and J. Qiu
Pages: 350-362
11. What and When Can We Gain From the Kernel Versions of C-Means Algorithm?
Author(s): N. R. Pal and K. Sarkar
Pages: 363-379
12. Dissipativity Analysis and Synthesis for Discrete-Time T–S Fuzzy Stochastic Systems With Time-Varying Delay
Author(s): L.Wu, X.Yang, and H.-K.Lam
Pages: 380-394
13. Making Use of Partial Knowledge About Hidden States in HMMs: An Approach Based on Belief Functions
Author(s): E.Ramasso and T.Denoeux
Pages: 395-405
14. Decentralized Fuzzy Observer-Based Output-Feedback Control for Nonlinear Large-Scale Systems: An LMI Approach
Author(s): G.B.Koo, J.B.Park, and Y.H.Joo
Pages: 406-419
15. L_p Consonant Approximations of Belief Functions
Author(s): F. Cuzzolin
Pages: 420-436
16. Adaptive Fuzzy Control for Multilateral Cooperative Teleoperation of Multiple Robotic Manipulators Under Random Network-Induced Delays
Author(s): Z. Li, Y. Xia, and F. Sun
Pages: 437-450
SHORT PAPERS
17. TSK Observers for Discrete Type-1 and Type-2 FuzzySystemsAuthor(s): M. S. Fadali and S. Jafarzadeh
Pages: 451-458
18. Robust H∞ Control of TS Fuzzy Time-Delay Systems via a New Sliding-Mode Control Scheme
Author(s): Q.Gao, G.Feng, Z.Xi, Y.Wang, and J.Qiu
Pages: 459-464
19. Toward Necessity of Parametric Conditions for Monotonic Fuzzy Systems
Author(s): J.-M. Won and F. Karray
Pages: 465-470
Thursday, March 27, 2014
Conference paper deadline: CEC 2015
The deadline for submitting papers to the IEEE Congress on Evolutionary Computation (IEEE CEC) 2015 is December 19, 2014. This conference will be held in Sendai, Japan, 25-28 May, 2015.
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Wednesday, March 26, 2014
Conference paper deadline: PRICAI 2014
The deadline for submitting papers to the 13th Pacific Rim International Conference on Artificial Intelligence (PRICAI) 2014 is June 29, 2014. This conference will be held in the Gold Coast, Australia, 1-5 December, 2014.
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conferences,
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Tuesday, March 25, 2014
Neural Networks new articles 17 March - 24 March
1. Stochastic nonlinear time series forecasting using time-delay reservoir computers: Performance and universality
Author(s): Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
2. New criterion of asymptotic stability for delay systems with time-varying structures and delays
Author(s): Bo Liu, Wenlian Lu, Tianping Chen
3. A systematic method for analyzing robust stability of interval neural networks with time-delays based on stability criteria
Author(s): Zhenyuan Guo, Jun Wang, Zheng Yan
Author(s): Lyudmila Grigoryeva, Julie Henriques, Laurent Larger, Juan-Pablo Ortega
2. New criterion of asymptotic stability for delay systems with time-varying structures and delays
Author(s): Bo Liu, Wenlian Lu, Tianping Chen
3. A systematic method for analyzing robust stability of interval neural networks with time-delays based on stability criteria
Author(s): Zhenyuan Guo, Jun Wang, Zheng Yan
Labels:
journals,
neural networks
Monday, March 24, 2014
Conference paper deadline: ICONIP 2014
The deadline for submitting papers to the 21st International Conference on Neural Information Processing (ICONIP) 2014 is May 2, 2014. This conference will be held in Kuching, Malaysia, 3-6 November, 2014.
Labels:
call for papers,
conferences,
deadline
Friday, March 21, 2014
Neural Networks new articles 10 March - 16 March
1. Learning invariant object recognition from temporal correlation in a hierarchical network
Author(s): Markus Lessmann, Rolf P. Würtz
2. Impulsive synchronization schemes of stochastic complex networks with switching topology: Average time approach
Author(s): Chaojie Li, Wenwu Yu, Tingwen Huang
Author(s): Markus Lessmann, Rolf P. Würtz
2. Impulsive synchronization schemes of stochastic complex networks with switching topology: Average time approach
Author(s): Chaojie Li, Wenwu Yu, Tingwen Huang
Labels:
journals,
neural networks
Thursday, March 20, 2014
Finding an academic job
Finding a job for any profession is difficult, but finding a job in
academia can be ridiculously hard. Since I finished my PhD ten years
ago, I've had two periods of unemployment, totalling more than six
months out of work. Since I was the sole income-earner for my family at
the time, those periods were particularly difficult and stressful to get
through, but I got through them, as much by luck as by design.
I've come across a collection of articles on finding academic jobs, that I wanted to share and comment on. I tend to agree with what most of them have to say, even though they're not specific to computational intelligence in particular or even computer science or engineering in general.
The first discusses whether you should even go for an academic job. For computer scientists it is probably easier to go into industry with a PhD than it is for other PhD graduates. The tech industry is always strong somewhere, and it is always growing, so there are always jobs to be had. In my own country of New Zealand, at any one time there are usually between two and three thousand vacancies in the IT sector, and that's out of a country of around four million.
The second article discusses ways to improve your chances of getting an academic job. The authors mention engaging with the community, publishing papers and emphasising transferable skills. I've actually had one supervisor tell me that there is nothing more important than publishing papers, while this article argues that too much publishing runs the risk of establishing nothing more than an unfocussed research record, and this article argues that teaching experience, including experience designing and administering courses, is very important for getting an academic job. Even though I was more interested in the research side of things during my Honours year, I still worked as a tutor for a database course, and during my post-grad years I tutored computational intelligence courses. Near the end of my studies, I worked full-time as a teaching fellow (I believe in the USA that would be Teaching Assistant, but I can't be sure) and did re-work and administer courses. I am quite certain that this experience helped me to get the job I have now.
Having decided to stay in academia, and done the ground-work to enter the academic profession, the next step is to find an academic job. When you've identified a job you are interested in, the first thing you must do it get your academic CV in order. There are several common mistakes you must avoid in this document, since one mistake is all it takes for a recruiter (who are not academics) to discard your entire application. The previous two articles have some very good pieces of advice for laying out your CV, and I have applied several of them to improve my own CV.
Things like career objective statements should also be left out of a CV. My current job means that I regularly receive unsolicited emails complete with CV from people wanting a teaching job in my department, and most of them have things like career objective statements that have nothing whatsoever to do with my department or any kind of teaching job. Nothing says "desperate blanket bombing" like failing to do even a minimum of research about the place you are sending your job application to.
The other major component of an application for an academic job is the cover letter. This should also be specific for the position you are applying for, it should cover all of the criteria mentioned in the job advertisement, and it should be short. If you make it too long and detailed, then you run the risk of boring the recruiter before they finish reading, which usually results in your application being thrown away.
If you have a compelling CV, and have written a very good cover letter that shows that you are very well suited to the job, then you might get an interview. This article talks about how to prepare for an interview. One of the points in it that I would emphasise is the need to do your research before the interview. One of the fundamental rules in the Art of War is "Know yourself, and know others, and you shall have one hundred victories in one hundred battles". This applies to interviews as well! Know who is going to be interviewing you: have they published with anyone you know? Is there any other connection? What relationship does their research have to yours? This article also has some tips on how to handle tricky interview questions. Some questions just can't be answered well, like the question I got once about how I demonstrated an awareness of diversity in the classroom (I'm from the whitest district in New Zealand and I married a Chinese, I think that shows a pretty good awareness of diversity). Obviously, some self-confidence is very important, and I've been lucky in that a couple of times some really good people have boosted my self-esteem just before interviews.
Usually, by the end of an interview, I know whether I've gotten the job or not, just by the way the interview went. If I have struggled with any of the questions, then I probably won't get it. If it's gone smoothly, then I know I've got a much better chance. There have been a couple of cases where the interview went well and I still didn't get the job, but those were years ago and for positions that were probably above my skill level at the time.
Job hunting is brutal, and academic positions invariably attract a lot of applications (especially New Zealand positions, as for some reason a lot of people want to move here). The last time I was out of work, I sent off two dozen applications, which resulted in three interviews, which led to two job offers. And that was with a PhD, four years teaching experience, almost five years post-doc experience, and more than forty publications. But, if you stick to it, you will find a job. It might not be the job you first had in mind when you started, but it will be just as good, and any job is good experience if you're clever about how you do it.
I've come across a collection of articles on finding academic jobs, that I wanted to share and comment on. I tend to agree with what most of them have to say, even though they're not specific to computational intelligence in particular or even computer science or engineering in general.
The first discusses whether you should even go for an academic job. For computer scientists it is probably easier to go into industry with a PhD than it is for other PhD graduates. The tech industry is always strong somewhere, and it is always growing, so there are always jobs to be had. In my own country of New Zealand, at any one time there are usually between two and three thousand vacancies in the IT sector, and that's out of a country of around four million.
The second article discusses ways to improve your chances of getting an academic job. The authors mention engaging with the community, publishing papers and emphasising transferable skills. I've actually had one supervisor tell me that there is nothing more important than publishing papers, while this article argues that too much publishing runs the risk of establishing nothing more than an unfocussed research record, and this article argues that teaching experience, including experience designing and administering courses, is very important for getting an academic job. Even though I was more interested in the research side of things during my Honours year, I still worked as a tutor for a database course, and during my post-grad years I tutored computational intelligence courses. Near the end of my studies, I worked full-time as a teaching fellow (I believe in the USA that would be Teaching Assistant, but I can't be sure) and did re-work and administer courses. I am quite certain that this experience helped me to get the job I have now.
Having decided to stay in academia, and done the ground-work to enter the academic profession, the next step is to find an academic job. When you've identified a job you are interested in, the first thing you must do it get your academic CV in order. There are several common mistakes you must avoid in this document, since one mistake is all it takes for a recruiter (who are not academics) to discard your entire application. The previous two articles have some very good pieces of advice for laying out your CV, and I have applied several of them to improve my own CV.
Things like career objective statements should also be left out of a CV. My current job means that I regularly receive unsolicited emails complete with CV from people wanting a teaching job in my department, and most of them have things like career objective statements that have nothing whatsoever to do with my department or any kind of teaching job. Nothing says "desperate blanket bombing" like failing to do even a minimum of research about the place you are sending your job application to.
The other major component of an application for an academic job is the cover letter. This should also be specific for the position you are applying for, it should cover all of the criteria mentioned in the job advertisement, and it should be short. If you make it too long and detailed, then you run the risk of boring the recruiter before they finish reading, which usually results in your application being thrown away.
If you have a compelling CV, and have written a very good cover letter that shows that you are very well suited to the job, then you might get an interview. This article talks about how to prepare for an interview. One of the points in it that I would emphasise is the need to do your research before the interview. One of the fundamental rules in the Art of War is "Know yourself, and know others, and you shall have one hundred victories in one hundred battles". This applies to interviews as well! Know who is going to be interviewing you: have they published with anyone you know? Is there any other connection? What relationship does their research have to yours? This article also has some tips on how to handle tricky interview questions. Some questions just can't be answered well, like the question I got once about how I demonstrated an awareness of diversity in the classroom (I'm from the whitest district in New Zealand and I married a Chinese, I think that shows a pretty good awareness of diversity). Obviously, some self-confidence is very important, and I've been lucky in that a couple of times some really good people have boosted my self-esteem just before interviews.
Usually, by the end of an interview, I know whether I've gotten the job or not, just by the way the interview went. If I have struggled with any of the questions, then I probably won't get it. If it's gone smoothly, then I know I've got a much better chance. There have been a couple of cases where the interview went well and I still didn't get the job, but those were years ago and for positions that were probably above my skill level at the time.
Job hunting is brutal, and academic positions invariably attract a lot of applications (especially New Zealand positions, as for some reason a lot of people want to move here). The last time I was out of work, I sent off two dozen applications, which resulted in three interviews, which led to two job offers. And that was with a PhD, four years teaching experience, almost five years post-doc experience, and more than forty publications. But, if you stick to it, you will find a job. It might not be the job you first had in mind when you started, but it will be just as good, and any job is good experience if you're clever about how you do it.
Labels:
career management
Wednesday, March 19, 2014
IEEE Transactions on Neural Networks and Learning Systems Volume 25, Number 4, April 2014
REGULAR PAPERS
1. Dynamic Uncertain Causality Graph for Knowledge Representation and Probabilistic Reasoning: Statistics Base, Matrix, and ApplicationAuthor(s): Q. Zhang, C. Dong, Y. Cui, and Z. Yang
Pages: 645-663
2. T2FELA: Type-2 Fuzzy Extreme Learning Algorithm for Fast Training of Interval Type-2 TSK Fuzzy Logic System
Author(s): Z. Deng, K.-S. Choi, L. Cao, and S. Wang
Pages: 664-676
3. Adaptive Quasi-Newton Algorithm for Source Extraction via CCA Approach
Author(s): W.-T. Zhang, S.-T. Lou, and D.-Z. Feng
Pages: 677-689
4. Lagrange Stability of Memristive Neural Networks With Discrete and Distributed Delays
Author(s): A. Wu and Z. Zeng
Pages: 690-703
5. Attractivity Analysis of Memristor-Based Cellular Neural Networks With Time-Varying Delays
Author(s): Z. Guo, J. Wang, and Z. Yan
Pages: 704-717
6. Novel Neural Control for a Class of Uncertain Pure-Feedback Systems
Author(s): Q. Shen, P. Shi, T. Zhang, and C.-C. Lim
Pages: 718-727
7. An Ordered-Patch-Based Image Classification Approach on the Image Grassmannian Manifold
Author(s): C. Xu, T. Wang, J. Gao, S. Cao, W. Tao, and F. Liu
Pages: 728-737
8. Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions
Author(s): S. Li, M. Fairbank, C. Johnson, D. C. Wunsch, E. Alonso, and J. L. Proaño
Pages: 738-750
9. A Stochastic Mean Field Model for an Excitatory and Inhibitory Synaptic Drive Cortical Neuronal Network
Author(s): Q. Hui, W. M. Haddad, J. M. Bailey, and T. Hayakawa
Pages: 751-763
10. RandomBoost: Simplified Multiclass Boosting Through Randomization
Author(s): S. Paisitkriangkrai, C. Shen, Q. Shi, and A. van den Hengel
Pages: 764-779
11. A Unified Learning Framework for Single Image Super-Resolution
Author(s): J. Yu, X. Gao, D. Tao, X. Li, and K. Zhang
Pages: 780-792
12. L1-Norm Kernel Discriminant Analysis via Bayes Error Bound Optimization for Robust Feature Extraction
Author(s): W. Zheng, Z. Lin, and H. Wang
Pages: 793-805
BRIEF PAPERS
13. Online Motor Fault Detection and Diagnosis Using a Hybrid FMM-CART ModelAuthor(s): M. Seera and C. P. Lim
Pages: 806-811
14. Feature-Based Ordering Algorithm for Data Presentation of Fuzzy ARTMAP Ensembles
Author(s): T. H. Oong and N. A. M. Isa
Pages: 812-818
16. Self-Organization in Autonomous, Recurrent, Firing-Rate CrossNets With Quasi-Hebbian Plasticity
Author(s): T. J. Walls and K. K. Likharev
Pages: 819-823
17. A Recurrent Neural Network for Solving Bilevel Linear Programming Problem
Author(s): X. He, C. Li, T. Huang, C. Li, and J. Huang
Pages: 824-829
18. Local Stability Analysis of Discrete-Time, Continuous-State, Complex-Valued Recurrent Neural Networks With Inner State Feedback
Author(s): M. Mostafa, W. G. Teich, and J. Lindner
Pages: 830-842
19. Sparse Bayesian Extreme Learning Machine for Multi-classification
Author(s): J. Luo, C.-M. Vong, and P.-K. Wong
Pages: 843
Labels:
IEEE TNNLS,
journals
Tuesday, March 18, 2014
IEEE Transactions on Autonomous Mental Development, Volume 6, Number 1, March 2014
1. An Approach to Subjective Computing: A Robot That Learns From Interaction With Humans
Author(s): P. Grüneberg and K. Suzuki
Pages: 5-18
2. LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning
Author(s): S. Franklin, T. Madl, S. D’Mello, and J. Snaider
Pages: 19-41
3. Development of First Social Referencing Skills: Emotional Interaction as a Way to Regulate Robot Behavior
Author(s): S. Boucenna, P. Gaussier, and L. Hafemeister
Pages: 42-55
4. Object Learning Through Active Exploration
Author(s): S. Ivaldi, S. M. Nguyen, N. Lyubova, A. Droniou, V. Padois, D. Filliat, P.-Y. Oudeyer, and O. Sigaud
Pages: 56-72
5. Erratum to "Modeling Cross-Modal Interactions in EarlyWord Learning"
Pages: 73
Author(s): P. Grüneberg and K. Suzuki
Pages: 5-18
2. LIDA: A Systems-level Architecture for Cognition, Emotion, and Learning
Author(s): S. Franklin, T. Madl, S. D’Mello, and J. Snaider
Pages: 19-41
3. Development of First Social Referencing Skills: Emotional Interaction as a Way to Regulate Robot Behavior
Author(s): S. Boucenna, P. Gaussier, and L. Hafemeister
Pages: 42-55
4. Object Learning Through Active Exploration
Author(s): S. Ivaldi, S. M. Nguyen, N. Lyubova, A. Droniou, V. Padois, D. Filliat, P.-Y. Oudeyer, and O. Sigaud
Pages: 56-72
5. Erratum to "Modeling Cross-Modal Interactions in EarlyWord Learning"
Pages: 73
Monday, March 17, 2014
IEEE Transactions on Computational Intelligence and AI in Games - Volume 6, Number 1, March 2014
1. General Self-Motivation and Strategy Identification: Case Studies Based on Sokoban and Pac-Man
Author(s): T. Anthony, D. Polani, and C. L. Nehaniv
Pages: 1-17
2. Passing a Hide-and-Seek Third-Person Turing Test
Author(s): A. Cenkner, V. Bulitko, M. Spetch, E. Legge, C. G. Anderson, and M. Brown
Pages: 18-30
3. Solving the Physical Traveling Salesman Problem: Tree Search and Macro Actions
Author(s): D. Perez, E. J. Powley, D. Whitehouse, P. Rohlfshagen, S. Samothrakis, P. I. Cowling, and S. M. Lucas
Pages: 31-45
4. Two Online Learning Playout Policies in Monte Carlo Go: An Application of Win/Loss States
Author(s): J. Basaldúa, S. Stewart, J. M. Moreno-Vega, and P. D. Drake
Pages: 46-54
5. DeepQA Jeopardy! Gamification: A Machine-Learning Perspective
Author(s): A. K. Baughman, W. Chuang, K. R. Dixon, Z. Benz, and J. Basilico
Pages: 55-66
6. A Micromanagement Task Allocation System for Real-Time Strategy Games
Author(s): K. D. Rogers and A. A. Skabar
Pages: 67-77
7. Procedural Generation of Dungeons
Author(s): R. van der Linden, R. Lopes, and R. Bidarra
Pages: 78-89
Author(s): T. Anthony, D. Polani, and C. L. Nehaniv
Pages: 1-17
2. Passing a Hide-and-Seek Third-Person Turing Test
Author(s): A. Cenkner, V. Bulitko, M. Spetch, E. Legge, C. G. Anderson, and M. Brown
Pages: 18-30
3. Solving the Physical Traveling Salesman Problem: Tree Search and Macro Actions
Author(s): D. Perez, E. J. Powley, D. Whitehouse, P. Rohlfshagen, S. Samothrakis, P. I. Cowling, and S. M. Lucas
Pages: 31-45
4. Two Online Learning Playout Policies in Monte Carlo Go: An Application of Win/Loss States
Author(s): J. Basaldúa, S. Stewart, J. M. Moreno-Vega, and P. D. Drake
Pages: 46-54
5. DeepQA Jeopardy! Gamification: A Machine-Learning Perspective
Author(s): A. K. Baughman, W. Chuang, K. R. Dixon, Z. Benz, and J. Basilico
Pages: 55-66
6. A Micromanagement Task Allocation System for Real-Time Strategy Games
Author(s): K. D. Rogers and A. A. Skabar
Pages: 67-77
7. Procedural Generation of Dungeons
Author(s): R. van der Linden, R. Lopes, and R. Bidarra
Pages: 78-89
Labels:
IEEE TCIAIG,
journals
Friday, March 14, 2014
Reminder: paper submission deadline for IEEE SSCI 2014
A reminder that the deadline for submitting papers to the IEEE Symposium Series on Computational Intelligence (SSCI) 2014 is 15 June 2014. This group of symposia will be held in Orlando, Florida, 9-12 December, 2014.
Labels:
call for papers,
conferences,
reminder
Tuesday, March 11, 2014
Neural Networks new articles 4 March - 10 March
1. Stable locality sensitive discriminant analysis for image recognition
Author(s): Quanxue Gao, Jingjing Liu, Kai Cui, Hailin Zhang, Xiaogang Wang
2. Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes
Author(s): Yuri Quintana-Pacheco, Daniel Ruiz-Fernández, Agustín Magrans-Rico
3. Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach
Author(s): Xian-Ming Zhang, Qing-Long Han
Author(s): Quanxue Gao, Jingjing Liu, Kai Cui, Hailin Zhang, Xiaogang Wang
2. Growing Neural Gas approach for obtaining homogeneous maps by restricting the insertion of new nodes
Author(s): Yuri Quintana-Pacheco, Daniel Ruiz-Fernández, Agustín Magrans-Rico
3. Global asymptotic stability analysis for delayed neural networks using a matrix-based quadratic convex approach
Author(s): Xian-Ming Zhang, Qing-Long Han
Labels:
journals,
neural networks
Friday, March 7, 2014
IEEE SMC 2014 Special Session: Autonomous Learning and Evolving Intelligence
Below is a call for papers for a special session in the 2014 IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC). This conference will be held in San Diego, California, October 5-8, 2014.
To achieve autonomous learning, a computer develops a form of intelligence that can evolve and adapt to its surroundings. A system that learns and evolves automatically should also operate in real-time. Currently DARPA have a challenge running for robots to operate autonomously in inhospitable environments; NSF is also recognising autonomous learning as a significant topic of research; large companies such as IBM, BT etc. also have programmes in autonomic computing and related disciplines. The objective of the proposed special session is to bring together people from academia and industry to introduce papers that look at addressing some of the fundamental problems or stumbling blocks found when a computer must learn for itself and evolve to it's surroundings.
University of Lancaster, UK
Submission of a full-length paper
May 25, 2014
Acceptance/Rejection notification
July 9, 2014
Final camera-ready paper submission
Autonomous Learning and Evolving Intelligence
Synopsis
The special session is focussed on addressing autonomous learning in computational systems in a setting where the role of the human is to merely to start/stop the process and monitor it online. It is a specific branch of machine learning, where the computer system is expected to learn for itself within a dynamically evolving and challenging environment complex processes without heuristic input or prior training.To achieve autonomous learning, a computer develops a form of intelligence that can evolve and adapt to its surroundings. A system that learns and evolves automatically should also operate in real-time. Currently DARPA have a challenge running for robots to operate autonomously in inhospitable environments; NSF is also recognising autonomous learning as a significant topic of research; large companies such as IBM, BT etc. also have programmes in autonomic computing and related disciplines. The objective of the proposed special session is to bring together people from academia and industry to introduce papers that look at addressing some of the fundamental problems or stumbling blocks found when a computer must learn for itself and evolve to it's surroundings.
Indicative Topics /Areas (not limited to)
- Autonomous Learning
- Autonomous Video Analytics
- Intelligence and Adaptive Systems
- Adaptive and Self-calibrating Sensor Systems
- Autonomous Fuzzy rule-based Systems
- Anomaly Detection
- Fault Detection and Identification
- Evolving Clustering
- Evolving Classification Methods
- Adaptive Behaviour Models
- Robotic Systems
Submission details
Papers should not exceed 8 pages in length, papers over 6 pages in length are charged extra per page (up to a max of 2). Manuscript for a Special Session should NOT be submitted in duplication to any other regular or special session and should be submitted to SMC 2014 main conference online submission system on SMC 2014 conference website. All submitted papers of Special Session have to undergo the same review process (a t least two reviewers). The technical reviewers for each Special Session paper will be members of the SMC 2014 Program Committee and qualified peer-reviewers to be nominated by the Special Session organizers.Special Session organizer
Plamen AngelovUniversity of Lancaster, UK
Important Dates
April 7, 2014Submission of a full-length paper
May 25, 2014
Acceptance/Rejection notification
July 9, 2014
Final camera-ready paper submission
Labels:
call for papers,
conferences,
special session
Thursday, March 6, 2014
Conference paper deadline: WCCS 14
The deadline for submitting abstracts to the World Congress on Complex Systems (WCCS) 2014 is 15 May, 2014. This conference will be held in Agadir, Morocco, November 10-14, 2014.
Labels:
call for papers,
conferences,
deadline
Wednesday, March 5, 2014
Neural Networks new articles 24 February - 2 March
1. An improved robust stability result for uncertain neural networks with multiple time delays
Author(s): Sabri Arik
2. Necessary and sufficient condition for multistability of neural networks evolving on a closed hypercube
Author(s): Mauro Di Marco, Mauro Forti, Massimo Grazzini, Luca Pancioni
3. Interaction of feedforward and feedback streams in visual cortex in a firing-rate model of columnar computations
Author(s): Tobias Brosch, Heiko Neumann
4. Solving the linear interval tolerance problem for weight initialization of neural networks
Author(s): S.P. Adam, D.A. Karras, G.D. Magoulas, M.N. Vrahatis
5. Further results on robustness analysis of global exponential stability of recurrent neural networks with time delays and random disturbances
Author(s): Weiwei Luo, Kai Zhong, Song Zhu, Yi Shen
Author(s): Sabri Arik
2. Necessary and sufficient condition for multistability of neural networks evolving on a closed hypercube
Author(s): Mauro Di Marco, Mauro Forti, Massimo Grazzini, Luca Pancioni
3. Interaction of feedforward and feedback streams in visual cortex in a firing-rate model of columnar computations
Author(s): Tobias Brosch, Heiko Neumann
4. Solving the linear interval tolerance problem for weight initialization of neural networks
Author(s): S.P. Adam, D.A. Karras, G.D. Magoulas, M.N. Vrahatis
5. Further results on robustness analysis of global exponential stability of recurrent neural networks with time delays and random disturbances
Author(s): Weiwei Luo, Kai Zhong, Song Zhu, Yi Shen
Labels:
journals,
neural networks
Tuesday, March 4, 2014
Evolving Systems Volume 5, Number 1, 2014
1. Editorial: Applications, results and future direction (EAIS 12)
Author(s): José Antonio Iglesias & Igor Škrjanc
2. A robust fuzzy adaptive law for evolving control systems
Author(s):Sašo Blažič , Igor Škrjanc & Drago Matko
3. Fault-tolerant gait learning and morphology optimization of a polymorphic walking robot
Author(s):David Johan Christensen , Jørgen Christian Larsen & Kasper Stoy
4. Elastic Adaptive Dynamics Methodology on Ontology Matching on Evolving Folksonomy Driven Environment
Author(s):Massimiliano Dal Mas
5. Dynamic learning in cognitive robotics through a procedural long term memory
Author(s):Francisco Bellas , Pilar Caamaño , Andrés Faiña & Richard J. Duro
6. Adaptive evolving strategy for dextrous robotic manipulation
Author(s):César Arismendi , David Álvarez , Santiago Garrido & Luis Moreno
Author(s): José Antonio Iglesias & Igor Škrjanc
2. A robust fuzzy adaptive law for evolving control systems
Author(s):Sašo Blažič , Igor Škrjanc & Drago Matko
3. Fault-tolerant gait learning and morphology optimization of a polymorphic walking robot
Author(s):David Johan Christensen , Jørgen Christian Larsen & Kasper Stoy
4. Elastic Adaptive Dynamics Methodology on Ontology Matching on Evolving Folksonomy Driven Environment
Author(s):Massimiliano Dal Mas
5. Dynamic learning in cognitive robotics through a procedural long term memory
Author(s):Francisco Bellas , Pilar Caamaño , Andrés Faiña & Richard J. Duro
6. Adaptive evolving strategy for dextrous robotic manipulation
Author(s):César Arismendi , David Álvarez , Santiago Garrido & Luis Moreno
Labels:
Evolving Systems,
journals
Monday, March 3, 2014
Neural Networks, Volume 52, Pages 1-76, April 2014
1. Pairwise constrained concept factorization for data representation
Pages: 1-17
Author(s): Yangcheng He, Hongtao Lu, Lei Huang, Saining Xie
2. Hybrid extreme rotation forest
Pages: 33-42
Author(s): Borja Ayerdi, Manuel Graña
3. Policy oscillation is overshooting
Pages: 43-61
Author(s): Paul Wagner
4. NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
Pages: 62-76
Author(s): Nikola K. Kasabov
5. Construction of a Boolean model of gene and protein regulatory network with memory
Pages: 18-24
Author(s): Meng Yang, Rui Li, Tianguang Chu
6. Nonsmooth finite-time stabilization of neural networks with discontinuous activations
Pages: 25-32
Author(s): Xiaoyang Liu, Ju H. Park, Nan Jiang, Jinde Cao
Pages: 1-17
Author(s): Yangcheng He, Hongtao Lu, Lei Huang, Saining Xie
2. Hybrid extreme rotation forest
Pages: 33-42
Author(s): Borja Ayerdi, Manuel Graña
3. Policy oscillation is overshooting
Pages: 43-61
Author(s): Paul Wagner
4. NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data
Pages: 62-76
Author(s): Nikola K. Kasabov
5. Construction of a Boolean model of gene and protein regulatory network with memory
Pages: 18-24
Author(s): Meng Yang, Rui Li, Tianguang Chu
6. Nonsmooth finite-time stabilization of neural networks with discontinuous activations
Pages: 25-32
Author(s): Xiaoyang Liu, Ju H. Park, Nan Jiang, Jinde Cao
Labels:
journals,
neural networks
Tuesday, February 25, 2014
Neural Networks new articles 17 February - 23 February
1. Fastest strategy to achieve given number of neuronal firing in theta model
Author(s): Jiaoyan Wang, Qingyun Wang, Guanrong Chen
2. Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays
Author(s): Jinde Cao, Ying Wan
Author(s): Jiaoyan Wang, Qingyun Wang, Guanrong Chen
2. Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays
Author(s): Jinde Cao, Ying Wan
Labels:
journals,
neural networks
Friday, February 21, 2014
IEEE Transactions on Neural Networks and Learning Systems: Volume 25, Issue 3, March 2014
1. A Survey on CPG-Inspired Control Models and System Implementation
Author(s): Junzhi Yu; Min Tan; Jian Chen; Jianwei Zhang
Pages: 441 - 456
2. Robust Model Predictive Control of Nonlinear Systems With Unmodeled Dynamics and Bounded Uncertainties Based on Neural Networks
Author(s): Zheng Yan; Jun Wang
Pages: 457 - 469
3. Multi-Level Fuzzy Min-Max Neural Network Classifier
Author(s): Reza Davtalab; Mir Hossein Dezfoulian; Muharram Mansoorizadeh
Pages: 470 - 482
4. Adaptive Identifier for Uncertain Complex Nonlinear Systems Based on Continuous Neural Networks
Author(s): Mariel Alfaro-Ponce; Amadeo Arguelles Cruz; Isaac Chairez
Pages: 483 - 494
5. Function Approximation Using Combined Unsupervised and Supervised Learning
Author(s): Peter Andras
Pages: 495 - 505
6. Active Learning of Pareto Fronts
Author(s): Paolo Campigotto; Andrea Passerini; Roberto Battiti
Pages: 506 - 519
7. Learning Harmonium Models With Infinite Latent Features
Author(s): Ning Chen; Jun Zhu; Fuchun Sun; Bo Zhang
Pages: 520 - 532
8. A Class of Quaternion Kalman Filters
Author(s): Cyrus Jahanchahi; Danilo P. Mandic
Pages: 533 - 544
9. Neural Network for Nonsmooth, Nonconvex Constrained Minimization Via Smooth Approximation
Author(s): Wei Bian; Xiaojun Chen
Pages: 545 - 556
10. Nonbinary Associative Memory With Exponential Pattern Retrieval Capacity and Iterative Learning
Author(s): Amir Hesam Salavati; K. Raj Kumar; Amin Shokrollahi
Pages: 557 - 570
11. A Constrained Backpropagation Approach for the Adaptive Solution of Partial Differential Equations
Author(s): Keith Rudd; Gianluca Di Muro; Silvia Ferrari
Pages: 571 - 584
12. A Robust and Scalable Neuromorphic Communication System by Combining Synaptic Time Multiplexing and MIMO-OFDM
Author(s): Narayan Srinivasa; Deying Zhang; Beayna Grigorian
Pages: 585 - 608
13. ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion From EEG Signal
Author(s): Reza Khosrowabadi; Chai Quek; Kai Keng Ang; Abdul Wahab
Pages: 609 - 620
14. Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems
Author(s): Derong Liu; Qinglai Wei
Pages: 621 - 634
15. Reinforcement Learning Output Feedback NN Control Using Deterministic Learning Technique
Author(s): Bin Xu; Chenguang Yang; Zhongke Shi
Pages: 635 - 641
Author(s): Junzhi Yu; Min Tan; Jian Chen; Jianwei Zhang
Pages: 441 - 456
2. Robust Model Predictive Control of Nonlinear Systems With Unmodeled Dynamics and Bounded Uncertainties Based on Neural Networks
Author(s): Zheng Yan; Jun Wang
Pages: 457 - 469
3. Multi-Level Fuzzy Min-Max Neural Network Classifier
Author(s): Reza Davtalab; Mir Hossein Dezfoulian; Muharram Mansoorizadeh
Pages: 470 - 482
4. Adaptive Identifier for Uncertain Complex Nonlinear Systems Based on Continuous Neural Networks
Author(s): Mariel Alfaro-Ponce; Amadeo Arguelles Cruz; Isaac Chairez
Pages: 483 - 494
5. Function Approximation Using Combined Unsupervised and Supervised Learning
Author(s): Peter Andras
Pages: 495 - 505
6. Active Learning of Pareto Fronts
Author(s): Paolo Campigotto; Andrea Passerini; Roberto Battiti
Pages: 506 - 519
7. Learning Harmonium Models With Infinite Latent Features
Author(s): Ning Chen; Jun Zhu; Fuchun Sun; Bo Zhang
Pages: 520 - 532
8. A Class of Quaternion Kalman Filters
Author(s): Cyrus Jahanchahi; Danilo P. Mandic
Pages: 533 - 544
9. Neural Network for Nonsmooth, Nonconvex Constrained Minimization Via Smooth Approximation
Author(s): Wei Bian; Xiaojun Chen
Pages: 545 - 556
10. Nonbinary Associative Memory With Exponential Pattern Retrieval Capacity and Iterative Learning
Author(s): Amir Hesam Salavati; K. Raj Kumar; Amin Shokrollahi
Pages: 557 - 570
11. A Constrained Backpropagation Approach for the Adaptive Solution of Partial Differential Equations
Author(s): Keith Rudd; Gianluca Di Muro; Silvia Ferrari
Pages: 571 - 584
12. A Robust and Scalable Neuromorphic Communication System by Combining Synaptic Time Multiplexing and MIMO-OFDM
Author(s): Narayan Srinivasa; Deying Zhang; Beayna Grigorian
Pages: 585 - 608
13. ERNN: A Biologically Inspired Feedforward Neural Network to Discriminate Emotion From EEG Signal
Author(s): Reza Khosrowabadi; Chai Quek; Kai Keng Ang; Abdul Wahab
Pages: 609 - 620
14. Policy Iteration Adaptive Dynamic Programming Algorithm for Discrete-Time Nonlinear Systems
Author(s): Derong Liu; Qinglai Wei
Pages: 621 - 634
15. Reinforcement Learning Output Feedback NN Control Using Deterministic Learning Technique
Author(s): Bin Xu; Chenguang Yang; Zhongke Shi
Pages: 635 - 641
Labels:
IEEE TNNLS,
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