Published January 2008 | Version v1
Journal article Metadata-only

More relaxed condition for dynamics of discrete time delayed Hopfield neural networks

Creators

  • 1. Liaoning Key Laboratory of Intelligent Information Processing, Dalian University Dalian 116622 (China)

Description

The dynamics of discrete time delayed Hopfield neural networks is investigated. By using a difference inequality combining with the linear matrix inequality, a sufficient condition ensuring global exponential stability of the unique equilibrium point of the networks is found. The result obtained holds not only for constant delay but also for time-varying delays

Availability note (English)

Available from http://dx.doi.org/10.1088/1674-1056/17/1/022

Additional details

Identifiers

DOI
10.1088/1674-1056/17/1/022;

Publishing Information

Journal Title
Chinese Physics. B
Journal Volume
17
Journal Issue
1
Journal Page Range
p. 125-128
ISSN
1674-1056

INIS

Country of Publication
China
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
44123583
Subject category
S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS;
Descriptors DEI
EQUILIBRIUM; MATRICES; NEURAL NETWORKS; STABILITY; TIME DELAY; TIME DEPENDENCE