Global exponential stability and existence of periodic solutions in BAM networks with delays and reaction-diffusion terms
Global exponential stability and existence of periodic solutions in BAM networks with delays and reaction-diffusion terms
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DOI：
10.1016/j.chaos.2004.04.011
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发表时间：
2005
影响因子：
7.8
通讯作者：
Q. Song;Jinde Cao
中科院分区：
文献类型：
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作者：
Q. Song;Jinde Cao
通过构造适当的李雅普诺夫泛函和一些分析技巧，研究了一类具有时滞和反应扩散项的双向联想记忆（BAM）神经网络的指数稳定性和周期解.给出了具有时滞和反应扩散项的BAM神经网络全局指数稳定和周期解存在的一般充分条件。这些条件都是以系统参数的形式给出的，对于具有时滞和反应扩散项的BAM神经网络的全局指数稳定和周期振荡的设计和应用具有重要的指导意义.
Both exponential stability and periodic solutions are considered for a class of bi-directional associative memory (BAM) neural networks with delays and reaction–diffusion terms by constructing suitable Lyapunov functional and some analysis techniques. The general sufficient conditions are given ensuring the global exponential stability and existence of periodic solutions of BAM neural networks with delays and reaction–diffusion terms. These presented conditions are in terms of system parameters and have important leading significance in the design and applications of globally exponentially stable and periodic oscillatory neural circuits for BAM with delays and reaction–diffusion terms.