Journal of Applied Mathematics

Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process

Weiwei Zhang and Linshan Wang

Full-text: Open access

Abstract

The robust stochastic stability for a class of uncertain neutral-type delayed neural networks driven by Wiener process is investigated. By utilizing the Lyapunov-Krasovskii functional and inequality technique, some sufficient criteria are presented in terms of linear matrix inequality (LMI) to ensure the stability of the system. A numerical example is given to illustrate the applicability of the result.

Article information

Source
J. Appl. Math., Volume 2012 (2012), Article ID 829594, 12 pages.

Dates
First available in Project Euclid: 15 March 2012

Permanent link to this document
https://projecteuclid.org/euclid.jam/1331817304

Digital Object Identifier
doi:10.1155/2012/829594

Mathematical Reviews number (MathSciNet)
MR2852853

Zentralblatt MATH identifier
1235.93196

Citation

Zhang, Weiwei; Wang, Linshan. Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process. J. Appl. Math. 2012 (2012), Article ID 829594, 12 pages. doi:10.1155/2012/829594. https://projecteuclid.org/euclid.jam/1331817304


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