Stability Analysis for Discrete-Time Stochastic Fuzzy Neural Networks with Mixed Delays

YaJun Li and Quanxin Zhu

Mathematical Problems in Engineering, 2019, vol. 2019, 1-13

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.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:8529053

DOI: 10.1155/2019/8529053

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