An Analysis on Global Exponential Stability of Hybrid BAM Neural Networks With Time-Varying Delays and Impulse

被引：0

作者：

Li, Yao-Tang ^{[1
]}

Wang, Jiyu ^{[1
]}

机构：

[1] Yunnan Univ, Sch Math & Stat, Kunming 650091, Yunnan, Peoples R China

来源：

SOUTHEAST ASIAN BULLETIN OF MATHEMATICS | 2010年 / 34卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Exponential stability; Bidirectional associative memory(BAM); Young in-equality; M-matrix; Time-varying delays; Impulse;

D O I：

暂无

中图分类号：

O1 [数学];

学科分类号：

0701 ; 070101 ;

摘要：

By utilizing the Lyapunov functional method, applying the homeomorphism theory and M-matrix theory, Young inequality technique and some analysis techniques, some sufficient conditions are obtained for the global exponential stability and existence of equilibrium points for hybrid bidirectional associative memory (BAM) neural networks subjected to impulsive state displacements at fixed instants of time. The results remove assumptions on boundedness, monotonicity or differentiability of the activation functions. It is shown that in some cases, the stability criteria can be easily checked. Finally, one illustrative example is also provided to demonstrate the effectiveness of the obtained results.

引用

页码：333 / 348

页数：16

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