Exponential synchronization of Markovian jumping chaotic neural networks with sampled-data and saturating actuators. (May 2017)

• Record Type: Journal Article
• Authors: Rakkiyappan, R.; Preethi Latha, V.; Zhu, Quanxin; Yao, Zhangsong
• Is Part Of: Nonlinear analysis. Volume 24(2017)
• Page Start: 28
• Page End: 44
• Publication Date: 2017-05
• Subjects: Saturating actuator -- Exponential synchronization -- Markovian jumping neural network -- Chaotic system -- Sampled-data -- Linear matrix inequality; Nonlinear functional analysis -- Periodicals; Analyse fonctionnelle non linéaire -- Périodiques; Nonlinear functional analysis; Periodicals; 515.7248
• DOI: 10.1016/j.nahs.2016.10.004
• Languages: English
• ISSNs: 1751-570X

Abstract

Abstract: This paper deals with the problem of exponential synchronization of Markovian jumping chaotic neural networks with saturating actuators using a sampled-data controller. By constructing a proper Lyapunov–Krasovskii functional (LKF) with triple integral terms, and employing Jensen's inequality, some new sufficient conditions for the exponential synchronization of considered chaotic neural networks are derived in terms of linear matrix inequalities (LMIs). The obtained LMIs can be easily solved by any of the available software. Finally, the numerical examples are provided to demonstrate the effectiveness of our theoretical results.