ROBUST SYNCHRONIZATION CRITERIA FOR RECURRENT NEURAL NETWORKS VIA LINEAR FEEDBACK-Reference-Cited by-同舟云学术

ROBUST SYNCHRONIZATION CRITERIA FOR RECURRENT NEURAL NETWORKS VIA LINEAR FEEDBACK

Published:2007-08 Issue:08 Volume:17 Page:2723-2738
ISSN:0218-1274
Container-title:International Journal of Bifurcation and Chaos
language:en
Short-container-title:Int. J. Bifurcation Chaos

Author:

HUANG XIA¹²,LAM JAMES³,CAO JINDE¹,XU SHENGYUAN⁴

Affiliation:

1. Department of Mathematics, Southeast University, Nanjing 210096, P. R. China

2. College of Information and Electrical Engineering, Shandong University of Science and Technology, Qingdao 266510, P. R. China

3. Department of Mechanical Engineering, University of Hong Kong, Hong Kong

4. Department of Automation, Nanjing University of Science and Technology, Nanjing 210094, P. R. China

Abstract

In this paper, the robust synchronization problem is addressed for recurrent neural networks with time-varying delay by linear feedback control. Robustness in the present paper is referred to as the allowance of parameters mismatch between the drive system and the response system. Sufficient conditions for robust synchronization with a synchronization error bound, expressed as linear matrix inequality (LMI), are derived based on Lyapunov–Krasovskii functionals. Both delay-dependent and delay-independent conditions are obtained. Two examples are given to illustrate the results.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modelling and Simulation,Engineering (miscellaneous)

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218127407018713

Reference36 articles.

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2. An improved global stability result for delayed cellular neural networks

3. Sequential synchronization of two Lorenz systems using active control

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