Global exponential stability for delayed cellular neural networks and estimate of exponential conver

来源 :Journal of Systems Engineering and Electronics | 被引量 : 0次 | 上传用户:sherry77677
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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 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 are special casses of the presented result.
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