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Global exponential stability for delayed cellular neural networks and estimate of exponential convergence rate 被引量:1

Global exponential stability for delayed cellular neural networks and estimate of exponential convergence rate
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摘要 Some sufficient conditions for the global exponential stability and lower bounds on the rate of exponential convergence of the cellular neural networks with delay (DCNNs) are obtained by means of a method based on delay differential inequality. The method, which does not make use of any Lyapunov functional, is simple and valid for the stability analysis of neural networks with delay. Some previously established results in this paper are shown to be special casses of the presented result. Some sufficient conditions for the global exponential stability and lower bounds on the rate of exponential convergence of the cellular neural networks with delay (DCNNs) are obtained by means of a method based on delay differential inequality. The method, which does not make use of any Lyapunov functional, is simple and valid for the stability analysis of neural networks with delay. Some previously established results in this paper are shown to be special casses of the presented result.
出处 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2004年第3期344-349,共6页 系统工程与电子技术(英文版)
关键词 global exponential stability convergence rate cellular neural networks with delay delay differential inequality. global exponential stability, convergence rate, cellular neural networks with delay, delay differential inequality.
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