Published February 22, 2010
| Version v1
Journal article
Improved delay-dependent exponential stability for uncertain stochastic neural networks with time-varying delays
Creators
- 1. School of Electrical Engineering, Chungbuk National University, Cheongju (Korea, Republic of)
- 2. School of Electronics Engineering, Daegu University, Kyongsan (Korea, Republic of)
- 3. Department of Electrical Engineering, Yeungnam University, Kyongsan (Korea, Republic of)
Description
This Letter investigates the problem of delay-dependent exponential stability analysis for uncertain stochastic neural networks with time-varying delay. Based on the Lyapunov stability theory, improved delay-dependent exponential stability criteria for the networks are established in terms of linear matrix inequalities (LMIs).
Availability note (English)
Available from http://dx.doi.org/10.1016/j.physleta.2010.01.007Additional details
Identifiers
- DOI
- 10.1016/j.physleta.2010.01.007;
- PII
- S0375-9601(10)00035-6;
Publishing Information
- Journal Title
- Physics Letters. A
- Journal Volume
- 374
- Journal Issue
- 10
- Journal Page Range
- p. 1232-1241
- ISSN
- 0375-9601
- CODEN
- PYLAAG
INIS
- Country of Publication
- Netherlands
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 41107872
- Subject category
- S97: MATHEMATICAL METHODS AND COMPUTING;
- Descriptors DEI
- LYAPUNOV METHOD; MATRICES; NEURAL NETWORKS; STABILITY; STOCHASTIC PROCESSES
- Descriptors DEC
- CALCULATION METHODS
Optional Information
- Copyright
- Copyright (c) 2010 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.