Robust Global Exponential Stability for Interval Reaction–Diffusion Hopfield Neural Networks With Distributed Delays

2007 ◽  
Vol 54 (12) ◽  
pp. 1115-1119 ◽  
Author(s):  
Jun Guo Lu
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Global Exponential Stability ◽  
Reaction Diffusion ◽  
Hopfield Neural Networks ◽  
Distributed Delays

NEW CRITERIA ON GLOBAL EXPONENTIAL STABILITY OF BAM NEURAL NETWORKS WITH DISTRIBUTED DELAYS AND REACTION-DIFFUSION TERMS

2007 ◽  
Vol 17 (01) ◽  
pp. 43-52 ◽  
Author(s):  
XUYANG LOU ◽  
BAOTONG CUI
Keyword(s):  
Neural Networks ◽  
Exponential Stability ◽  
Global Exponential Stability ◽  
Reaction Diffusion ◽  
Kernel Functions ◽  
Distributed Delays ◽  
Analysis Technique ◽  
Inequality Technique ◽  
New Criteria ◽  
Theoretical Results

This paper presents new theoretical results on global exponential stability of bi-directional associative memory neural networks with distributed delays and reaction-diffusion terms based on the inequality technique, Lyapunov functional, and analysis technique. The results remove the usual assumption that the activation functions are of monotonous or differential character. Exponential converging velocity index is estimated, which depends on the delay kernel functions and system parameters. Finally, two numerical examples are given to show the validity and feasibility of our results.

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