Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/83496
Citations | ||
Scopus | Web of Science® | Altmetric |
---|---|---|
?
|
?
|
Type: | Journal article |
Title: | A new criterion for exponential stability of uncertain stochastic neural networks with mixed delays |
Author: | Zhang, J. Shi, P. Qiu, J. Yang, H. |
Citation: | Mathematical and Computer Modelling, 2008; 47(9-10):1042-1051 |
Publisher: | Pergamon-Elsevier Science Ltd |
Issue Date: | 2008 |
ISSN: | 0895-7177 |
Statement of Responsibility: | Jinhui Zhang, Peng Shi, Jiqing Qiu, Hongjiu Yang |
Abstract: | This paper deals with the problem of exponential stability for a class of uncertain stochastic neural networks with both discrete and distributed delays (also called mixed delays). The system possesses time-varying and norm-bounded uncertainties. Based on Lyapunov–Krasovskii functional and stochastic analysis approaches, new stability criteria are presented in terms of linear matrix inequalities to guarantee the delayed neural networks to be robustly exponentially stable in the mean square for all admissible parameter uncertainties. Numerical examples are given to illustrate the effectiveness of the developed techniques. |
Keywords: | Stochastic neural networks Time delays Exponential stability Linear matrix inequalities (LMIs) Norm-bounded uncertainties |
Rights: | © 2007 Elsevier Ltd. All rights reserved. |
DOI: | 10.1016/j.mcm.2007.05.014 |
Published version: | http://dx.doi.org/10.1016/j.mcm.2007.05.014 |
Appears in Collections: | Aurora harvest 4 Electrical and Electronic Engineering publications |
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.