Global and Robust Stability of Interval Hopfield Neural Networks with Time-Varying Delays-Reference-Cited by-同舟云学术

Global and Robust Stability of Interval Hopfield Neural Networks with Time-Varying Delays

Published:2003-06 Issue:03 Volume:13 Page:171-182
ISSN:0129-0657
Container-title:International Journal of Neural Systems
language:en
Short-container-title:Int. J. Neur. Syst.

Author:

Liao Xiaofeng¹²,Wang Jun³,Cao Jinde⁴

Affiliation:

1. Department of Computer Science and Engineering, Chongqing University, Chongqing 400044, P. R. China

2. Department of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China

3. Department of Automation and Computer-Aided Engineering, The Chinese University of Hong Kong, China

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

Abstract

In this paper, we investigate the problem of global and robust stability of a class of interval Hopfield neural networks that have time-varying delays. Some criteria for the global and robust stability of such networks are derived, by means of constructing suitable Lyapunov functionals for the networks. As a by-product, for the conventional Hopfield neural networks with time-varying delays, we also obtain some new criteria for their global and asymptotic stability.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computer Networks and Communications,General Medicine

Link

https://www.worldscientific.com/doi/pdf/10.1142/S012906570300142X

Reference18 articles.

1. Neural networks and physical systems with emergent collective computational abilities.

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3. Stability in asymmetric Hopfield nets with transmission delays

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5. A note on stability of analog neural networks with time delays

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