New criteria on delay-dependent stability for discrete-time neural networks with time-varying delays

Authors:
O. M. Kwon;M. J. Park;Ju H. Park;S. M. Lee;E. J. Cha
Affiliations:
-;-;-;-;-
Venue:
Neurocomputing
Year:
2013

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Abstract

In this paper, the problem of delay-dependent stability for discrete-time neural networks with time-varying delays is investigated. By constructing a newly augmented Lyapunov-Krasovskii functional, a sufficient condition for guaranteeing the asymptotic stability of the concerned network is derived in the framework of linear matrix inequalities. Also, a further improved stability condition is developed by proposing a new activation condition which has not been considered in the literature. Two numerical examples are given to illustrate the effectiveness of the proposed methods.