4.6 Article

Delay-interval-dependent passivity analysis of stochastic neural networks with Markovian jumping parameters and time delay in the leakage term

期刊

NONLINEAR ANALYSIS-HYBRID SYSTEMS
卷 22, 期 -, 页码 262-275

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.nahs.2016.05.002

关键词

Passivity analysis; Stochastic neural network; Markovian jumping parameters; Leakage delay; Linear matrix inequality

资金

  1. National Natural Science Foundation of China [61374080]
  2. Alexander von Humboldt Foundation of Germany [CHN/1163390]
  3. Qing Lan Project of Jiangsu
  4. Priority Academic Program Development of Jiangsu Higher Education Institutions

向作者/读者索取更多资源

In this paper, the problem of passivity analysis is investigated for a class of stochastic neural networks with Markovian jumping parameters and time delay in the leakage term. The discrete delay is assumed to be time-varying and belongs to,a given interval, which means that the lower and upper bounds of interval time-varying delays are available. By constructing appropriate Lyapunov-Krasovskii functionals, and employing Newton-Leibniz formulation and the free weighting matrix method, several delay-dependent criteria for checking the passivity of the addressed neural networks are established in terms of linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two examples are given to show the effectiveness and less conservatism of the proposed criteria. (C) 2016 Elsevier Ltd. All rights reserved.

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