Robust stability analysis for fuzzy stochastic Hopfield neural networks with time–varying delays

Authors : Gopalakrishnan N

Pages : 1285-1309

Doi:10.31801/cfsuasmas.769920

View : 28 | Download : 9

Publication Date : 2020-12-31

Article Type : Research Paper

Abstract :This paper investigates the delay-dependent robust stability problem of fuzzy stochastic Hopfield neural networks with random timevarying delays. Moreover, in this paper, the stochastic delay is assumed to satisfy a certain probability distribution. By introducing a stochastic variable with Bernoulli distribution, the neural networks with random time delays is transformed into one with deterministic delays and stochastic parameters. Based on a LyapunovKrasovskii functional and stochastic analysis approach, delay-probability-distribution-dependent stability criteria have been derived in terms of linear matrix inequalities insert ignore into journalissuearticles values(LMIs);, which can be checked easily by the LMI control toolbox. Finally two numerical examples are given to illustrate the effectiveness of the theoretical results.
Keywords : Hopfield neural networks, Linear matrix inequality, Stochastic system, Timevarying delays

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