Published November 30, 2009 | Version v1
Journal article Metadata-only

Global exponential stability of fuzzy BAM neural networks with time-varying delays

Creators

  • 1. School of Mathematical Science and Computing Technology, Central South University, Changsha, Hunan 410083 (China) and Basic Science Department, Hunan Institute of Technology, Hengyang, Hunan 421002 (China)
  • 2. Basic Science Department, Hunan Institute of Technology, Hengyang, Hunan 421002 (China)

Description

In this paper, a class of fuzzy bidirectional associated memory (BAM) neural networks with time-varying delays are studied. Employing fixed point theorem, matrix theory and inequality analysis, some sufficient conditions are established for the existence, uniqueness and global exponential stability of equilibrium point. The sufficient conditions are easy to verify at pattern recognition and automatic control. Finally, an example is given to show feasibility and effectiveness of our results.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.chaos.2009.03.116

Additional details

Identifiers

DOI
10.1016/j.chaos.2009.03.116;
PII
S0960-0779(09)00283-5;

Publishing Information

Journal Title
Chaos, Solitons and Fractals
Journal Volume
42
Journal Issue
4
Journal Page Range
p. 2239-2245
ISSN
0960-0779

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
41020649
Subject category
S97: MATHEMATICAL METHODS AND COMPUTING;
Descriptors DEI
CONTROL THEORY; EQUILIBRIUM; FUZZY LOGIC; MATRICES; NEURAL NETWORKS; PATTERN RECOGNITION; STABILITY
Descriptors DEC
MATHEMATICAL LOGIC

Optional Information

Copyright
Copyright (c) 2009 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.