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Robust Stability Criteria for Uncertain Stochastic Cellular Neural Networks with Time Delays

Qiu, Jiqing and Gao, Zhifeng and 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.

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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.

Item Type: Book Section
ISBN: 0769528821, 9780769528823
Uncontrolled Keywords: ResPubID18961, Lyapunov methods, asymptotic stability, cellular neural nets, time delays, linear matrix inequalities, stochastic systems, uncertain systems
Subjects: FOR Classification > 0906 Electrical and Electronic Engineering
Faculty/School/Research Centre/Department > Institute for Logistics and Supply Chain Management (ILSCM)
FOR Classification > 0199 Other Mathematical Sciences Information Systems
Depositing User: VUIR
Date Deposited: 18 Jan 2014 08:27
Last Modified: 18 Jan 2014 08:27
URI: http://vuir.vu.edu.au/id/eprint/6376
DOI: 10.1109/ICICIC.2007.503
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Citations in Scopus: 0 - View on Scopus

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