A switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay

Advances in Difference Equations

Grienggrai Rajchakit¹  Piyapong Niamsup²  Manlika Rajchakit³ 

[1]Center of Excellence in Mathematics, CHE, Bangkok, Thailand

[2]Deparment of Mathematics, Faculty of Science, Chiang Mai University, Chiangmai, Thailand

[3]Division of Mathematics and Statistics, Faculty of Science, Maejo University, Chiangmai, Thailand

关键词: neural networks;    switching design;    exponential stability;    interval time-varying delays;    Lyapunov function;    linear matrix inequalities;   

DOI  :  10.1186/1687-1847-2013-44

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

This paper studies the problem for exponential stability of switched recurrent neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessarily differentiable. By constructing a set of argumented Lyapunov-Krasovskii functionals combined with the Newton-Leibniz formula, a switching rule for exponential stability of switched recurrent neural networks with interval time-varying delay is designed via linear matrix inequalities, and new sufficient conditions for the exponential stability of switched recurrent neural networks with interval time-varying delay via linear matrix inequalities (LMIs) are derived. A numerical example is given to illustrate the effectiveness of the obtained result.

【 授权许可】

CC BY