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2006•Mathematica ApplicataRequires access

Global Exponential Stability of Cellular Neural Networks with Delay

Zhao Wei-rui

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Abstract

Employing Lyapunov functional and the technique of integral inequality,the paper presented a new theorem to judge the global exponential stability of cellular neural networks with time delay.A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed cellular neural networks.Those conditions are less restrictive than those given in the earlier references.

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What this paper is about

Employing Lyapunov functional and the technique of integral inequality,the paper presented a new theorem to judge the global exponential stability of cellular neural networks with time delay.A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed cellular neural networks.Those conditions are less restrictive than those given in the earlier references.

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Available abstract

Employing Lyapunov functional and the technique of integral inequality,the paper presented a new theorem to judge the global exponential stability of cellular neural networks with time delay.A comparison between our results and the previous results admits that our results establish a new set of stability criteria for delayed cellular neural networks.Those conditions are less restrictive than those given in the earlier references.

Key concepts: Exponential stability, Cellular neural network, Artificial neural network, Stability (learning theory), Mathematics, Set (abstract data type), Applied mathematics, Lyapunov function

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