New Delay-Dependent Stability Criteria for Recurrent Neural Networks with Time-Varying Delays

Ze Rong Ren; Xiang Jun Xie

doi:10.4028/www.scientific.net/AMM.513-517.922

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 513-517New Delay-Dependent Stability Criteria for...

New Delay-Dependent Stability Criteria for Recurrent Neural Networks with Time-Varying Delays

Abstract:

This paper is concerned with the problem of delay-dependent asymptotic stability criterion for recurrent neural networks with time-varying delays. A new Lyapunov functional is introduced by considering the information of neuron activation functions adequately. By using the improved delay-partitioning method and reciprocally convex approach, a less conservative stability criterion is obtained in terms of linear matrix inequalities (LMIs). A numerical example is finally given to illustrate the effectiveness of the derived method.

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Periodical:

Applied Mechanics and Materials (Volumes 513-517)

Pages:

922-926

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.513-517.922

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Online since:

February 2014

Authors:

Ze Rong Ren*, Xiang Jun Xie

Keywords:

Delay-Dependent Stability, Linear Matrix Inequality (LMI), Neural Network (NN), Time-Varying Delays

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