Exponential Stability of Periodic Solutions for Inertial Type BAM Cohen-Grossberg Neural Networks
Joint Authors
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-05-19
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
The existence and exponential stability of periodic solutions for inertial type BAM Cohen-Grossberg neural networks are investigated.
First, by properly choosing variable substitution, the system is transformed to first order differential equation.
Second, some sufficient conditions that ensure the existence and exponential stability of periodic solutions for the system are obtained by constructing suitable Lyapunov functional and using differential mean value theorem and inequality technique.
Finally, two examples are given to illustrate the effectiveness of the results.
American Psychological Association (APA)
Miao, Chunfang& Ke, Yunquan. 2014. Exponential Stability of Periodic Solutions for Inertial Type BAM Cohen-Grossberg Neural Networks. Abstract and Applied Analysis،Vol. 2014, no. 2014, pp.1-19.
https://search.emarefa.net/detail/BIM-1014921
Modern Language Association (MLA)
Miao, Chunfang& Ke, Yunquan. Exponential Stability of Periodic Solutions for Inertial Type BAM Cohen-Grossberg Neural Networks. Abstract and Applied Analysis No. 2014 (2014), pp.1-19.
https://search.emarefa.net/detail/BIM-1014921
American Medical Association (AMA)
Miao, Chunfang& Ke, Yunquan. Exponential Stability of Periodic Solutions for Inertial Type BAM Cohen-Grossberg Neural Networks. Abstract and Applied Analysis. 2014. Vol. 2014, no. 2014, pp.1-19.
https://search.emarefa.net/detail/BIM-1014921
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1014921