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 the equilibrium point of a class of neutral-type neural networks with time-varying delays. By dividing the variation interval of the time delay into two subintervals with equal length, a more general type of Lyapunov functionals is defined. Following the idea of convex combination and free-weighting matrices method, new delay-dependent stability criteria are presented in terms of linear matrix inequalities (LMIs). Three examples are also given to illustrate the effectiveness and less conservativeness of our proposed conditions than some previous ones.
关键词：Global robust exponential stability; neutral;type neural networks; Jensen integral inequality; linear matrix inequality(LMI); free;weighting matrix
