期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2014
卷号：11
期号：1
出版社：IJCSI Press
摘要：The existence, uniqueness and global robust exponential stability is analyzed for a class of uncertain neutral-type bidirectional associative memory (BAM) neural networks with time-varying delays. Without assuming the boundedness of the activation functions, by constructing a novel class of augmented Lyapunov-Krasovskii functional, new relaxed delay-dependent stability criteria of the unique equilibrium point are presented in terms of linear matrix inequalities (LMIs). Following the idea of convex combination and free-weighting matrices method, less conser-vative results are obtained. Two examples are given to illustrate the effectiveness of our proposed conditions.
