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EXPONENTIAL STABILITY OF REACTION–DIFFUSION FUZZY RECURRENT NEURAL NETWORKS WITH TIME-VARYING DELAYS

QINGHUA ZHOU

Department of Mathematics, Zhaoqing University, Zhaoqing 526061, P. R. China

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LI WAN

Department of Mathematics, Huazhong University of Science and Technology, Wuhan 430074, P. R. China

Department of Mathematics and Physics, Wuhan University of Science and Engineering, Wuhan 430073, P. R. China

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JIANHUA SUN

Department of Mathematics, Nanjing University, Nanjing 210008, P. R. China

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https://doi.org/10.1142/S0218127407018890Cited by:7 (Source: Crossref)

Abstract

Exponential stability of reaction–diffusion fuzzy recurrent neural networks (RDFRNNs) with time-varying delays are considered. By using the method of variational parameters, M-matrix properties and inequality technique, some delay-independent or delay-dependent sufficient conditions for guaranteeing the exponential stability of an equilibrium solution are obtained. One example is given to demonstrate the theoretical results.

This work was supported in part by the National Natural Science Foundation of China under Grant 10471059, the Natural Science Foundation of Jiangsu Province under Grant BK2001024.

Keywords:

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