Novel criteria for mean square stability of stochastic delayed neural networks

Title:

Novel criteria for mean square stability of stochastic delayed neural networks

Creator:

Sun , Yonghui and Cao, Jinde

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:be66d8f9-eceb-4331-bf87-555a9436bf64
uuid:be66d8f9-eceb-4331-bf87-555a9436bf64

Subject:

Stochastic neural networks, time-varying delay, mean square exponential stability, linear matrix inequality, and Brownian motion

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper investigates the mean square stability of a class of stochastic neural networks with time-varying delays. By virtue of the stochastic analysis method and linear matrix inequality (LMI) approach, a new sufficient condition is proposed where the feasibility of the conditions can be readily checked by the Matlab LMI control toolbox. Moreover, our method has the advantage of removing the restrictions on the time varying delays, so the derived results are less conservative than the previous works. A numerical example with simulations are provided to illustrate the effectiveness of the developed results.

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 | 2008 Volume:18 | Number:3

Harvested from:

CDK

Metadata only:

false