Stability Analysis for Discrete-Time Stochastic Fuzzy Neural Networks with Mixed Delays. (14th February 2019)

• Record Type: Journal Article
• Authors: Li, YaJun; Zhu, Quanxin
• Other Names: De Luca Alessandro Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2019(2019)
• Publication Date: 2019-02-14
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2019/8529053
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : This paper is concerned with the stability problem of a class of discrete-time stochastic fuzzy neural networks with mixed delays. New Lyapunov-Krasovskii functions are proposed and free weight matrices are introduced. The novel sufficient conditions for the stability of discrete-time stochastic fuzzy neural networks with mixed delays are established in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to illustrate the effectiveness and benefits of the proposed method.