CFP: IEEE TNNLS special issue on "New Developments in Neural Network Structures for Signal Processing, Autonomous Decision, and Adaptive Control"

There has been continuously increasing interest in applying neural networks to identification and adaptive control of practical systems that are characterized by nonlinearity, uncertainty, communication constraints, and complexity. The past few years have witnessed a variety of new developments in neural-network-based approaches for behavior learning, information processing, autonomous decision, and system control. Biologically inspired neural network structures can significantly enhance the capabilities of information processing, control and computational performance. New discoveries in neurocognitive psychology, sociology, and elsewhere reveal new neurological learning structures with more powerful capabilities in complex problem solving and fast decision in dynamic environments.  The goal of the special issue is to consolidate recent new developments in neural network structures for signal processing, autonomous decision, and adaptive control with application to complex systems. It welcomes contributions from a wide range of research aspects relevant to the topic, including neural computing, adaptive control, cooperative control, autonomous decision systems, mathematical and computational models, neuropsychology decision and control, algorithms, simulation, applications and/or case studies.

SCOPE OF THE SPECIAL ISSUE

We invite original contributions related to new neural network structures and methods, adaptive neural network control, from theories, algorithms, modelling to experimental studies and applications. Topics include but are not limited to:

• Bio-inspired neural network structures for signal processing
• Cognitive computing and intelligent control
• Fast satisficing decision & control based on risk, gist and environmental cues
• Cooperative control using neural network structures
• Brain-like control design and applications
• New neural network topologies from neurocognitive psychology studies
• Neurocomputing structures for fast decision and control in dynamic environments
• Neural-adaptive learning in distributed multi-agent systems
• Spike timing-based learning algorithms with hierarchical/complex architectures
• Autonomous decision and control using neural structures
• Memory-based reasoning, prediction and control

Important Dates

31 Mar 2015 – Deadline for manuscript submission
31 May 2015 – Notification of authors
31 June 2015 – Deadline for submission of revised manuscripts
31 July 2015 – Final decision of acceptance
Nov. 2015 – Tentative Publication Date

Guest Editors

• Y.D. Song, Chongqing University, China, ydsong@cqu.edu.cn 
• F.L. Lewis, University of Texas at Arlington, USA
• Marios Polycarpou, University of Cyprus
• Danil Prokhorov, Toyota Research Institute North America, Ann Arbor, MI.
• Dongbin Zhao, Institute of Automation, Chinese Academy of Sciences, Beijing

Submission Instructions

1. Read the information for Authors at http://cis.ieee.org/tnnls
2. Submit your manuscript by 31 March 2015 at the TNNLS webpage (http://mc.manuscriptcentral.com/tnnls) and follow the submission procedure. Please, clearly indicate on the first page of the manuscript and in the cover letter that the manuscript has been submitted to the special issue on New Developments in Neural Network Structures for Signal Processing, Autonomous Decision, and Adaptive Control . Send also an email to guest editor Y.D. Song with subject “TNNLS special issue submission” to notify about your submission.