GLOBAL EXPONENTIAL STABILITY OF HIGH-ORDER BAM NEURAL NETWORKS WITH REACTION–DIFFUSION TERMS-Reference-Cited by-同舟云学术

GLOBAL EXPONENTIAL STABILITY OF HIGH-ORDER BAM NEURAL NETWORKS WITH REACTION–DIFFUSION TERMS

Published:2010-10 Issue:10 Volume:20 Page:3209-3223
ISSN:0218-1274
Container-title:International Journal of Bifurcation and Chaos
language:en
Short-container-title:Int. J. Bifurcation Chaos

Author:

ZHOU FENG-YAN¹,MA CHENG-RONG²

Affiliation:

1. Department of Mathematics, Shaoxing University, Shaoxing, Zhejiang 312000, P. R. China

2. Department of Mathematics, Zhejiang Industry Polytechnic College, Zhejiang 312000, P. R. China

Abstract

The global exponential stability is studied for a class of high-order bi-directional associative memory (BAM) neural networks with time delays and reaction–diffusion terms. By constructing suitable Lyapunov functional, using differential mean value theorem and homeomorphism, several sufficient conditions guaranteeing the existence, uniqueness and global exponential stability of high-order BAM neural networks with time delays and reaction–diffusion terms are given. Two illustrative examples are also given in the end to show the effectiveness of our results.

Publisher

World Scientific Pub Co Pte Lt

Subject

Applied Mathematics,Modeling and Simulation,Engineering (miscellaneous)

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218127410027635

Reference16 articles.

1. Global asymptotic stability of delayed bi-directional associative memory neural networks

2. Exponential stability of delayed bi-directional associative memory networks

3. Exponential stability of high-order bidirectional associative memory neural networks with time delays

4. Exponential stability of BAM neural networks with transmission delays

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