期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2008
卷号：8
期号：8
页码：255-263
出版社：International Journal of Computer Science and Network Security
摘要：In this paper, the global exponential stability is investigated for the discrete-time uncertain stochastic bidirectional associate memory neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By utilizing suitable Lyapunov?Krasovsky functional and using stochastic analysis theory and inequality technique, several sufficient conditions for checking the global robust exponential stability of the addressed neural networks are obtained in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. An example is given to show the effectiveness and less conservatism of the proposed criteria.
