Novel stochastic stability conditions of fuzzy neural networks with Markovian jumping parameters under impulsive perturbations

Title:

Novel stochastic stability conditions of fuzzy neural networks with Markovian jumping parameters under impulsive perturbations

Creator:

Zhang, Y. and Zheng, C. -D.

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:572512a6-a151-430d-b821-4fa861fd6cc6
uuid:572512a6-a151-430d-b821-4fa861fd6cc6
doi:10.14311/NNW.2016.26.001

Subject:

impulse, fuzzy neural networks, Markovian jumping, linear convex combination technique, and reciprocal convex combination

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

This paper investigates the stochastic stability of fuzzy neural networks with Markovian jumping parameters and mixed delays under impulsive per- turbations in mean square. The mixed delays consist of time-varying delay and continuously distributed delay. By employing a new Lyapunov-Krasovskii functional, linear convex combination technique, a novel reciprocal convex lemma and the free-weight matrix method, two novel sufficient conditions are derived to ensure the stochastic asymptotic stability of the equilibrium point of the considered networks in mean square. The proposed results, which are expressed in terms of linear matrix inequalities, can be easily checked via Matlab LMI Toolbox. Finally, two numerical examples are given to demonstrate the effectiveness and less conservativeness of our theoretical results over existing literature.

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 | 2016 Volume:26 | Number:1

Harvested from:

CDK

Metadata only:

false