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：2010
卷号：7
期号：1
页码：32-41
出版社：IJCSI Press
摘要：The stability and convergence of the neural networks are the fundamental characteristics in the Hopfield type networks. Since time delay is ubiquitous in most physical and biological systems, more attention is being made for the delayed neural networks. The inclusion of time delay into a neural model is natural due to the finite transmission time of the interactions. The stability analysis of the neural networks depends on the Lyapunov function and hence it must be constructed for the given system. In this paper we have made an attempt to establish the logarithmic stability of the impulsive delayed neural networks by constructing suitable Lyapunov function.
关键词：Hopfield type Neural Network; Time varying delays; Logarithmic Stability; Lyapunov function
