Title :
Novel robust stability criteria for interval-delayed Hopfield neural networks
Author :
Liao, Xiaofeng ; Wong, Kwok-Wo ; Wu, Zhongfu ; Chen, Guanrong
Author_Institution :
Dept. of Comput. Sci. & Eng., Chongqing Univ., China
fDate :
11/1/2001 12:00:00 AM
Abstract :
In this paper, some novel criteria for the global robust stability of a class of interval Hopfield neural networks with constant delays are given. Based on several new Lyapunov functionals, delay-independent criteria are provided to guarantee the global robust stability of such systems. For conventional Hopfield neural networks with constant delays, some new criteria for their global asymptotic stability are also easily obtained. All the results obtained are generalizations of some recent results reported in the literature for neural networks with constant delays. Numerical examples are also given to show the correctness of the analysis
Keywords :
Hopfield neural nets; Lyapunov methods; asymptotic stability; delays; stability criteria; Lyapunov functionals; constant delays; delay-independent criteria; global asymptotic stability; global robust stability; interval Hopfield neural networks; positive constant; stability bounds; Application software; Asymptotic stability; Computer science; Delay effects; Fluctuations; Hopfield neural networks; Information processing; Neural networks; Robust stability; Very large scale integration;
Journal_Title :
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
