Robust Stochastic Stability Analysis for Uncertain Neutral-Type Delayed Neural Networks Driven by Wiener Process
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.
Permanent link to this document: http://projecteuclid.org/euclid.jam/1331817304
Digital Object Identifier: doi:10.1155/2012/829594
Mathematical Reviews number (MathSciNet): MR2852853
Zentralblatt MATH identifier: 1235.93196
Journal of Applied Mathematics