Neurodynamic System Theory and Applications
1Department of Mathematics, Southeast University, Nanjing, China
2Department of Mathematics and Statistics, University of Strathclyde, Glasgow, UK
3School of Information & Control, Nanjing University of Information Science & Technology, Nanjing, China
Neurodynamic System Theory and Applications
Description
As neurodynamic systems have a wide range of applications in such fields as optimization, linear and nonlinear programming, associative memory, pattern recognition, computer vision, and so on, there has arisen, for seeking powerful theoretical supports of such applications, an urgent requirement for intensive research on neurodynamics theory, including convergence, stability, oscillation, bifurcation, and chaos.
Mathematical work on neurodynamics has increased in recent years. In view of some inevitable practical problems, including delay, stochastic disturbance, diffusion, and abrupt change, nowadays various neurodynamic systems have been formed, for example, delayed neural networks, stochastic neural networks, impulsive neural networks, reaction-diffusion neural networks, fuzzy neural networks, and so forth. The theory study of all these mathematical frameworks will pave the way for a more comprehensive understanding of the dynamic states of neural networks and therefore is of great significances for future realistic modeling studies of the brain.
This special issue is focused on the theory and applications of neurodynamic systems. This special issue will become an international forum for researchers to summarize the most recent developments and ideas in the field, with a special emphasis given to the technical and observational results obtained within the last five years. Potential topics include, but are not limited to:
- Delayed neural systems
- Stochastic neural systems
- Impulsive neural systems
- Reaction-diffusion neural systems
- Fuzzy neural systems
- Evolutionary neural systems
- Mathematical modeling of neural systems
- Neurodynamic optimization and adaptive dynamic programming
- Cognitive models
- Pattern recognition
- Neural network applications
Before submission authors should carefully read over the journal's Author Guidelines, which are located at http://www.hindawi.com/journals/aaa/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/aaa/nsta/ according to the following timetable: