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Mathematical Problems in Engineering
Volume 2014 (2014), Article ID 963081, 12 pages
http://dx.doi.org/10.1155/2014/963081
Research Article

Robust Adaptive Exponential Synchronization of Stochastic Perturbed Chaotic Delayed Neural Networks with Parametric Uncertainties

1School of Automation and Electronic Information, Sichuan University of Science & Engineering, Sichuan 643000, China
2Institute of Nonlinear Science and Engineering Computing, Sichuan University of Science & Engineering, Sichuan 643000, China

Received 27 December 2013; Revised 23 May 2014; Accepted 23 May 2014; Published 23 June 2014

Academic Editor: Yang Tang

Copyright © 2014 Yang Fang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper investigates the robust adaptive exponential synchronization in mean square of stochastic perturbed chaotic delayed neural networks with nonidentical parametric uncertainties. A robust adaptive feedback controller is proposed based on Gronwally’s inequality, drive-response concept, and adaptive feedback control technique with the update laws of nonidentical parametric uncertainties as well as linear matrix inequality (LMI) approach. The sufficient conditions for robust adaptive exponential synchronization in mean square of uncoupled uncertain stochastic chaotic delayed neural networks are derived in terms of linear matrix inequalities (LMIs). The effect of nonidentical uncertain parameter uncertainties is suppressed by the designed robust adaptive feedback controller rapidly. A numerical example is provided to validate the effectiveness of the proposed method.