Published February 13, 2006 | Version v1
Journal article

Global exponential robust stability of reaction-diffusion interval neural networks with time-varying delays

  • 1. Departament of Mathematics, Ocean University of China, Qingdao 266071 (China) and Departament of Mathematics, Liaocheng University, Liaocheng 252059 (China)
  • 2. Chemical College, Anshan University of Science and Technology, Anshan 114000 (China)

Description

The authors discuss the existence of the equilibrium point and its global exponential robust stability for reaction-diffusion interval neural networks with time-varying delays by means of the topological degree theory and Lyapunov-functional method. Since the diffusion phenomena, time delay and the perturbation due to noises as well as some unforced man-made faults could not be ignored in neural networks, the model presented here is close to the actual systems, and the sufficient conditions on global exponential robust stability established in this Letter, which are easily verifiable, have a wider adaptive range

Additional details

Identifiers

DOI
10.1016/j.physleta.2005.10.031;
PII
S0375-9601(05)01597-5;

Publishing Information

Journal Title
Physics Letters. A
Journal Volume
350
Journal Issue
5-6
Journal Page Range
p. 342-348
ISSN
0375-9601
CODEN
PYLAAG

INIS

Country of Publication
Netherlands
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
37066282
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
EQUILIBRIUM; LYAPUNOV METHOD; NEURAL NETWORKS; NOISE; PERTURBATION THEORY; STABILITY; TIME DELAY; TOPOLOGY
Descriptors DEC
CALCULATION METHODS; MATHEMATICS

Optional Information

Copyright
Copyright (c) 2005 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.