Globally Exponential Stability of Impulsive Neural Networks with Given Convergence Rate
Joint Authors
Liu, Chengyan
Li, Xiaodi
Fu, Xilin
Source
Advances in Artificial Neural Systems
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-05-27
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper deals with the stability problem for a class of impulsive neural networks.
Some sufficient conditions which can guarantee the globally exponential stability of the addressed models with given convergence rate are derived by using Lyapunov function and impulsive analysis techniques.
Finally, an example is given to show the effectiveness of the obtained results.
American Psychological Association (APA)
Liu, Chengyan& Li, Xiaodi& Fu, Xilin. 2013. Globally Exponential Stability of Impulsive Neural Networks with Given Convergence Rate. Advances in Artificial Neural Systems،Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-507247
Modern Language Association (MLA)
Liu, Chengyan…[et al.]. Globally Exponential Stability of Impulsive Neural Networks with Given Convergence Rate. Advances in Artificial Neural Systems No. 2013 (2013), pp.1-5.
https://search.emarefa.net/detail/BIM-507247
American Medical Association (AMA)
Liu, Chengyan& Li, Xiaodi& Fu, Xilin. Globally Exponential Stability of Impulsive Neural Networks with Given Convergence Rate. Advances in Artificial Neural Systems. 2013. Vol. 2013, no. 2013, pp.1-5.
https://search.emarefa.net/detail/BIM-507247
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-507247
