Robust Stability Analysis of Neutral-Type Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

被引：0
作者：
Feng, Wei [1 ,2 ]
Yang, Simon X. [1 ,3 ]
Wu, Haixia [1 ,2 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 400044, Peoples R China
[2] Chongqing Univ Educ, Dept Math & Informat Engn, Chongqing 400065, Peoples R China
[3] Univ Guelph, Sch Engn, Guelph, ON N1G 2W1, Canada
来源：
ABSTRACT AND APPLIED ANALYSIS | 2014年
基金：
中国国家自然科学基金;
关键词：
GLOBAL EXPONENTIAL STABILITY; ASYMPTOTIC STABILITY; ACTIVATION FUNCTIONS; DISTRIBUTED DELAYS; CRITERION; TERMS; NORM;
D O I：
10.1155/2014/560861
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
The global asymptotic robust stability of equilibrium is considered for neutral-type hybrid bidirectional associative memory neural networks with time-varying delays and parameters uncertainties. The results we obtained in this paper are delay-derivative-dependent and establish various relationships between the network parameters only. Therefore, the results of this paper are applicable to a larger class of neural networks and can be easily verified when compared with the previously reported literature results. Two numerical examples are illustrated to verify our results.
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页数：12
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