Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-31
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
This work addresses the stability study for stochastic cellular neural networks with time-varying delays.
By utilizing the new research technique of the fixed point theory, we find some new and concise sufficient conditions ensuring the existence and uniqueness as well as mean-square global exponential stability of the solution.
The presented algebraic stability criteria are easily checked and do not require the differentiability of delays.
The paper is finally ended with an example to show the effectiveness of the obtained results.
American Psychological Association (APA)
Yao, Tianxiang& Lai, Xianghong. 2014. Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-477396
Modern Language Association (MLA)
Yao, Tianxiang& Lai, Xianghong. Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method. Journal of Applied Mathematics No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-477396
American Medical Association (AMA)
Yao, Tianxiang& Lai, Xianghong. Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-477396
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-477396