Robust Stability Criteria for Uncertain Stochastic Cellular Neural Networks with Time Delays
Qiu, Jiqing, Gao, Zhifeng, Wang, Jufang and Shi, Peng (2007) Robust Stability Criteria for Uncertain Stochastic Cellular Neural Networks with Time Delays. In: Second International Conference on Innovative Computing, Information and Control, 2007. ICICIC '07. IEEE, New York, N.Y., pp. 556-559.
Abstract
In this paper, the global robust asymptotic stability problem is considered for stochastic cellular neural networks with time delays and parameter uncertainties. The aim of this paper is to establish easily verifiable conditions under which the stochastic cellular neural networks is globally robustly asymptotically stable in the mean square for all admissible parameter uncertainties. Base on Lyapunov- Krasovskii functional and stochastic analysis approaches, a linear matrix inequality (LMI) approach is developed to derive the stability criteria. A numerical example is provided to illustrate the effectiveness and applicability of the proposed criteria.
Dimensions Badge
Altmetric Badge
Item type | Book Section |
URI | https://vuir.vu.edu.au/id/eprint/6376 |
DOI | 10.1109/ICICIC.2007.503 |
Official URL | http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arn... |
ISBN | 0769528821, 9780769528823 |
Subjects | Historical > FOR Classification > 0906 Electrical and Electronic Engineering Historical > Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM) Historical > FOR Classification > 0199 Other Mathematical Sciences Information Systems |
Keywords | ResPubID18961, Lyapunov methods, asymptotic stability, cellular neural nets, time delays, linear matrix inequalities, stochastic systems, uncertain systems |
Citations in Scopus | 1 - View on Scopus |
Download/View statistics | View download statistics for this item |