Exponential Synchronization of Stochastic Reaction-Diffusion Fuzzy Cohen-Grossberg Neural Networks With Time-Varying Delays Via Periodically Intermittent Control

Author:

Gan Qintao1,Li Yang2

Affiliation:

1. Department of Basic Science, Shijiazhuang Mechanical Engineering College, 97 Heping West Road, Shijiazhuang, Hebei Province 050003, China e-mail:

2. Department of Vehicle and Electrical Engineering, Shijiazhuang Mechanical Engineering College, Shijiazhuang, Hebei Province 050003, China

Abstract

In this paper, the exponential synchronization problem for fuzzy Cohen-Grossberg neural networks with time-varying delays, stochastic noise disturbance, and reaction-diffusion effects are investigated. By introducing a novel Lyapunov-Krasovskii functional with the idea of delay partitioning, a periodically intermittent controller is developed to derive sufficient conditions ensuring the addressed neural networks to be exponentially synchronized in terms of p-norm. The results extend and improve upon earlier work. A numerical example is provided to show the effectiveness of the proposed theories.

Publisher

ASME International

Subject

Computer Science Applications,Mechanical Engineering,Instrumentation,Information Systems,Control and Systems Engineering

Reference47 articles.

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3. Robust Exponential Stability of Uncertain Fuzzy Cohen-Grossberg Neural Networks With Time-Varying Delays;Fuzzy Sets Syst.,2010

4. Dynamics of a Class of Cohen-Grossberg Neural Networks With Time-Varying Delays;Nonlinear Anal.: Real World Appl.,2007

5. Stability Analysis for Cohen-Grossberg Neural Networks With Time-Varying Delays Via LMI Approach;Expert Syst. Appl.,2011

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