Published July 21, 2008
| Version v1
Journal article
Robust exponential stability for delayed uncertain Hopfield neural networks with Markovian jumping parameters
Creators
- 1. Department of Mathematics, Bohai University, Jinzhou 121000 (China)
- 2. Institute of Complexity Science, Qingdao University, Qingdao 266071 (China)
Description
This Letter is concerned with delay-dependent robust exponential mean square stability for delayed uncertain Hopfield neural networks with Markovian jumping parameters. Time delays here are discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii stability theory, delay-dependent stability conditions are derived in terms of linear matrix inequalities (LMIs). Finally, numerical examples are given to illustrate the effectiveness of the proposed method
Availability note (English)
Available from http://dx.doi.org/10.1016/j.physleta.2008.05.034Additional details
Identifiers
- DOI
- 10.1016/j.physleta.2008.05.034;
- PII
- S0375-9601(08)00772-X;
Publishing Information
- Journal Title
- Physics Letters. A
- Journal Volume
- 372
- Journal Issue
- 30
- Journal Page Range
- p. 4996-5003
- ISSN
- 0375-9601
- CODEN
- PYLAAG
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 40046601
- Subject category
- S71: CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; S99: GENERAL AND MISCELLANEOUS;
- Descriptors DEI
- LYAPUNOV METHOD; MARKOV PROCESS; MATRICES; NEURAL NETWORKS; NUMERICAL ANALYSIS; STABILITY; TIME DELAY
- Descriptors DEC
- CALCULATION METHODS; MATHEMATICS; STOCHASTIC PROCESSES
Optional Information
- Copyright
- Copyright (c) 2008 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.