Dissipativity Analysis of Complex-Valued Stochastic Neural Networks With Time-Varying Delays

被引：3
|
作者：
Liu, Meijuan [1 ]
Wang, Xiangrong [1 ]
Zhang, Ziye [1 ]
Wang, Zhen [1 ]
机构：
[1] Shandong Univ Sci & Technol, Coll Math & Syst Sci, Qingdao 266590, Peoples R China
来源：
IEEE ACCESS | 2019年 / 7卷
基金：
中国国家自然科学基金;
关键词：
Complex-valued stochastic neural network; time-varying delays; dissipativity; Ito formula; OUTPUT-FEEDBACK CONTROL; STABILITY ANALYSIS; DYNAMICAL-SYSTEMS; DISCRETE; MODEL;
D O I：
10.1109/ACCESS.2019.2953244
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper considers the dissipativity analysis problem for complex-valued stochastic neural networks (CVSNNs) with time-varying delays. By constructing the Lyapunov functions, using Jensen inequality and stochastic analysis techniques, several sufficient conditions for the exponential dissipativity and (Q, R, S)-dissipativity in the mean square are obtained in terms of linear matrix inequalities (LMIs). Compared with the existing ones, in our work, some results which are more applicable for CVSNNs with time-varying delays case are derived. Finally, two numerical examples are provided to illustrate the effectiveness and improvement of our theoretical results.
引用
收藏
页码：165076 / 165087
页数：12
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