Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales
Joint Authors
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-08-22
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The existence of equilibrium solutions to reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales is proved by the topological degree theory and M-matrix method.
Under some sufficient conditions, we obtain the uniqueness and global exponential stability of equilibrium solution to reaction-diffusion recurrent neural networks with Dirichlet boundary conditions on time scales by constructing suitable Lyapunov functional and inequality skills.
One example is given to illustrate the effectiveness of our results.
American Psychological Association (APA)
Zhao, Kaihong& Li, Yongkun. 2010. Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales. Discrete Dynamics in Nature and Society،Vol. 2010, no. 2010, pp.1-12.
https://search.emarefa.net/detail/BIM-486052
Modern Language Association (MLA)
Zhao, Kaihong& Li, Yongkun. Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales. Discrete Dynamics in Nature and Society No. 2010 (2010), pp.1-12.
https://search.emarefa.net/detail/BIM-486052
American Medical Association (AMA)
Zhao, Kaihong& Li, Yongkun. Existence and Global Exponential Stability of Equilibrium Solution to Reaction-Diffusion Recurrent Neural Networks on Time Scales. Discrete Dynamics in Nature and Society. 2010. Vol. 2010, no. 2010, pp.1-12.
https://search.emarefa.net/detail/BIM-486052
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-486052