Exponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-12-15
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
This paper studies the asymptotic behavior for a class of delayed reaction-diffusion Hopfield neural networks driven by finite-dimensional Wiener processes.
Some new sufficient conditions are established to guarantee the mean square exponential stability of this system by using Poincaré’s inequality and stochastic analysis technique.
The proof of the almost surely exponential stability for this system is carried out by using the Burkholder-Davis-Gundy inequality, the Chebyshev inequality and the Borel-Cantelli lemma.
Finally, an example is given to illustrate the effectiveness of the proposed approach, and the simulation is also given by using the Matlab.
American Psychological Association (APA)
Liang, Xiao& Wang, Linshan. 2011. Exponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays. Journal of Applied Mathematics،Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-993566
Modern Language Association (MLA)
Liang, Xiao& Wang, Linshan. Exponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays. Journal of Applied Mathematics No. 2012 (2012), pp.1-12.
https://search.emarefa.net/detail/BIM-993566
American Medical Association (AMA)
Liang, Xiao& Wang, Linshan. Exponential Stability for a Class of Stochastic Reaction-Diffusion Hopfield Neural Networks with Delays. Journal of Applied Mathematics. 2011. Vol. 2012, no. 2012, pp.1-12.
https://search.emarefa.net/detail/BIM-993566
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-993566