New results on stability of stochastic neural networks with Markovian switching and mode-dependent time-varying delays

Title:

New results on stability of stochastic neural networks with Markovian switching and mode-dependent time-varying delays

Creator:

Li, Peijuan, Wang, Yueying, Zhou, Pingfang, Wang, Quanbao, and Duan, Dengping

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:cae14e2f-01f1-4b62-a381-e68e28c9fe61
uuid:cae14e2f-01f1-4b62-a381-e68e28c9fe61
doi:10.14311/NNW.2014.24.006

Subject:

Lyapunov-Krasovskii functional, Markovian swithcing, mode-dependent time delays, neural networks, and stochastic system

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper is concerned with the problem of exponential stability for a class of stochastic neural networks with Markovian switching and mode-dependent interval time-varying delays. A novel Lyapunov-Krasovskii functional is introduced with the idea of delay-partitioning, and a new exponential stability criterion is derived based on the new functional and free-weighting matrix method. This new criterion proves to be less conservative than the most existing results. Numerical examples are presented to illustrate the effectiveness of the proposed method.

Language:

English

Rights:

http://creativecommons.org/publicdomain/mark/1.0/
policy:public

Source:

Neural network world: international journal on neural and mass-parallel computing and information systems | 2014 Volume:24 | Number:1

Harvested from:

CDK

Metadata only:

false