2009•Unpublished venueRequires access

A new global asymptotic stability result for delayed cellular neural networks

Jing Liu, Ce Zhang

Abstract

This paper studies the problem of global asymptotic stability for delayed cellular neural networks(DCNNs). A new stability condition is obtained by utilizing the Lyapunov functional method and the matrix inequality approach. This condition is less restrictive and generalizes some of the previous stability results derived in the literature.

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Available abstract

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