Mean-Square Exponential Stability Analysis of Stochastic Neural Networks with Time-Varying Delays via Fixed Point Method

Joint Authors

Yao, Tianxiang
Lai, Xianghong

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

Mathematics

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