Delay-dependent exponential stability results for uncertain stochastic Hopfield neural networks with interval time-varying delays

被引:0
|
作者
Pradeep, C. [1 ]
Vinodkumar, A. [2 ]
Rakkiyappan, R. [3 ]
机构
[1] Sri Ramakrishna Inst Technol, Dept Sci & Humanities, Coimbatore 641010, Tamil Nadu, India
[2] PSG Coll Technol, Dept Math & Comp Applicat, Coimbatore 641004, Tamil Nadu, India
[3] Bharathiar Univ, Dept Math, Coimbatore 641046, Tamil Nadu, India
关键词
D O I
10.1007/s40065-012-0005-6
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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-weightingmatrices. Finally, three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed LMI conditions.
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页码:227 / 239
页数:13
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