Exponential Stability Results of Discrete-Time Stochastic Neural Networks with Time-Varying Delays
Author
Source
Mathematical Problems in Engineering
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-07
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
An innovative stability analysis approach for a class of discrete-time stochastic neural networks (DSNNs) with time-varying delays is developed.
By constructing a novel piecewise Lyapunov-Krasovskii functional candidate, a new sum inequality is presented to deal with sum items without ignoring any useful items, the model transformation is no longer needed, and the free weighting matrices are added to reduce the conservatism in the derivation of our results, so the improvement of computational efficiency can be expected.
Numerical examples and simulations are also given to show the effectiveness and less conservatism of the proposed criteria.
American Psychological Association (APA)
Li, Yajun. 2013. Exponential Stability Results of Discrete-Time Stochastic Neural Networks with Time-Varying Delays. Mathematical Problems in Engineering،Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1009537
Modern Language Association (MLA)
Li, Yajun. Exponential Stability Results of Discrete-Time Stochastic Neural Networks with Time-Varying Delays. Mathematical Problems in Engineering No. 2013 (2013), pp.1-10.
https://search.emarefa.net/detail/BIM-1009537
American Medical Association (AMA)
Li, Yajun. Exponential Stability Results of Discrete-Time Stochastic Neural Networks with Time-Varying Delays. Mathematical Problems in Engineering. 2013. Vol. 2013, no. 2013, pp.1-10.
https://search.emarefa.net/detail/BIM-1009537
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1009537