Dissipativity analysis of discrete-time Markovian jumping neural networks with time-varying delays

被引：5
|
作者：
Ali, M. Syed [1 ]
Meenakshi, K. [1 ]
Gunasekaran, N. [1 ]
Murugan, Kadarkarai [2 ,3 ]
机构：
[1] Thiruvalluvar Univ, Dept Math, Vellore, Tamil Nadu, India
[2] Bharathiar Univ, Sch Life Sci, Div Entomol, Dept Zool, Coimbatore, Tamil Nadu, India
[3] Thiruvalluvar Univ, Vellore, Tamil Nadu, India
来源：
JOURNAL OF DIFFERENCE EQUATIONS AND APPLICATIONS | 2018年 / 24卷 / 06期
关键词：
Dissipativity; discrete-time; neural networks; Markovian jumping; time-varying delays; DISTRIBUTED DELAYS; PERIODIC-SOLUTIONS; STATE ESTIMATION; STABILITY; SYSTEMS;
D O I：
10.1080/10236198.2018.1433171
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
This paper investigates the problem of dissipativity analysis for discrete- time Markovian jumping neural networks with time- varying delays. Based on an appropriate Lyapunov- Krasovskii functional and by using the latest free- weighting matrix method, a sufficient condition is established to ensure that the neural networks under consideration is strictly (Q, S, R)-. - dissipative. The derived conditions are presented in terms of linear matrix inequalities. A numerical example is presented to illustrate the effectiveness of the proposed results.
引用
收藏
页码：859 / 871
页数：13
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