New results for global robust asymptotic stability of BAM neural networks with time-varying delays

被引：18
作者：
Yuan, Yufa [1 ]
Li, Xiaolin [1 ]
机构：
[1] Shanghai Univ, Dept Math, Shanghai 200444, Peoples R China
来源：
NEUROCOMPUTING | 2010年 / 74卷 / 1-3期
基金：
美国国家科学基金会;
关键词：
BAM neural network; Global robust stability; Time varing delays; Lyapunov functionals; EXPONENTIAL STABILITY; CRITERIA;
D O I：
10.1016/j.neucom.2010.03.007
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper the global robust asymptotic stability for a class of delayed bidirectional associative memory (BAM) neural networks with interval uncertainty is studied Some less conservative conditions are presented for the BAM neural networks with multiple time-varing delays based on the Lyapunov functional approach We also give one example to demonstrate the applicability and effectiveness of our results and compare the results with the previous robust stability results derived in the literature (C) 2010 Elsevier B V All rights reserved
引用
收藏
页码：337 / 342
页数：6
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