Global exponential stability analysis of fuzzy BAM neural networks with time-varying delays

Authors:
Xuyang Lou;Baotong Cui
Affiliations:
(Correspd. louxuyang28945@163.com/ btcui@vip.sohu.com) School of Communication and Control Engineering, Southern Yangtze University, 1800 Lihu Rd.,Wuxi, Jiangsu 214122, P.R. China;School of Communication and Control Engineering, Southern Yangtze University, 1800 Lihu Rd.,Wuxi, Jiangsu 214122, P.R. China
Venue:
International Journal of Hybrid Intelligent Systems
Year:
2007

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Abstract

In this paper, the stability problem of Takagi-Sugeno fuzzy BAM neural networks with time-varying delays is considered. Firstly, this model is established as a modified Takagi-Sugeno fuzzy model in which the consequent parts are composed of a set of BAM neural networks with time-varying delays. Secondly, a globally exponentially stable condition is presented in terms of linear matrix inequalities, which can be easily solved by some standard numerical packages. Finally, two numerical examples are given to illustrate the effectiveness of the theoretical results.