Delay-interval-dependent passivity analysis of stochastic neural networks with Markovian jumping parameters and time delay in the leakage term. (November 2016)

• Record Type: Journal Article
• Authors: Senthilraj, S.; Raja, R.; Zhu, Quanxin; Samidurai, R.; Yao, Zhangsong
• Is Part Of: Nonlinear analysis. Volume 22(2016)
• Page Start: 262
• Page End: 275
• Publication Date: 2016-11
• Subjects: Passivity analysis -- Stochastic neural network -- Markovian jumping parameters -- Leakage delay -- Linear matrix inequality; Nonlinear functional analysis -- Periodicals; Analyse fonctionnelle non linéaire -- Périodiques; Nonlinear functional analysis; Periodicals; 515.7248
• DOI: 10.1016/j.nahs.2016.05.002
• Languages: English
• ISSNs: 1751-570X

Abstract

Abstract: 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.