2001Unpublished venueRequires access

Global asymptotic stability of delayed cellular neural networks

Zhi Gong

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Abstract

Further global asymptotic stability of a class of delayed cellular neural networks has been analyzed by means of Lyapunov functional method and new inequality technique and obtained a new sufficient criteria. These criteria are of theoretical and applicable important significance in the design of globally stable networks.

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What this paper is about

Further global asymptotic stability of a class of delayed cellular neural networks has been analyzed by means of Lyapunov functional method and new inequality technique and obtained a new sufficient criteria. These criteria are of theoretical and applicable important significance in the design of globally stable networks.

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Available abstract

Further global asymptotic stability of a class of delayed cellular neural networks has been analyzed by means of Lyapunov functional method and new inequality technique and obtained a new sufficient criteria. These criteria are of theoretical and applicable important significance in the design of globally stable networks.

Key concepts: Exponential stability, Cellular neural network, Artificial neural network, Stability (learning theory), Class (philosophy), Mathematics, Lyapunov function, Control theory (sociology)

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