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

Year 2020, Volume: 69 Issue: 2, 1285 - 1309, 31.12.2020

Gopalakrishnan N

https://doi.org/10.31801/cfsuasmas.769920

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 (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, Time–varying delays

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