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Delay-Dependent Exponential Stability Results for Uncertain Stochastic Hopfield Neural Networks with Interval Time-varying Delays

Publication Type : Journal Article

Publisher : Arabian Journal of Mathematics

Source : Arabian Journal of Mathematics, Volume 1, Number 2, p.227–239 (2012)

Url : http://dx.doi.org/10.1007/s40065-012-0005-6

Campus : Coimbatore

School : School of Engineering

Department : Mathematics

Year : 2012

Abstract : This paper is concerned with stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded and the delay is assumed to be time varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Both the cases of the time-varying delays which may be differentiable and may not be differentiable are considered in this paper. Based on the Lyapunov–Krasovskii functional and stochastic stability theory, delay/interval-dependent stability criteria are obtained in terms of linear matrix inequalities. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), by introducing some free-weighting matrices. Finally, three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed LMI conditions.

Cite this Research Publication : C. Pradeep, Dr. Vinodkumar A., and Rakkiyappan, R., “Delay-Dependent Exponential Stability Results for Uncertain Stochastic Hopfield Neural Networks with Interval Time-varying Delays”, Arabian Journal of Mathematics, vol. 1, pp. 227–239, 2012.

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