4.6 Article

Passivity analysis of stochastic neural networks with leakage delay and Markovian jumping parameters

Journal

NEUROCOMPUTING
Volume 218, Issue -, Pages 139-145

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.neucom.2016.08.062

Keywords

Delayed neural networks; Leakage term; Lyapunov functional; Markovian jumping parameters; Passivity; Stochastic disturbance; Time-varying delays

Funding

  1. Department of Science and Technology(DST) [SR/FTP/MS-039/2011]

Ask authors/readers for more resources

The problem of passivity analysis of stochastic neural networks with leakage delay and Markovian jumping parameters is considered in this article. By utilizing the Lyapunov functional method, the Ito differential rule and matrix analysis techniques, we establish sufficient criterion such that the stochastic neural networks is passive in the sense of expectation. The derived criteria are expressed in terms of linear matrix inequalities that can be easily checked by using the standard numerical software. Illustrative examples are presented to demonstrate the effectiveness and usefulness of the proposed results. (C) 2016 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available