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Attractor and Boundedness of Switched Stochastic Cohen-Grossberg Neural Networks
Joint Authors
Cao, Jie
Wang, Peng
Huang, Chuangxia
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-19, 19 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-05-19
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Abstract EN
We address the problem of stochastic attractor and boundedness of a class of switched Cohen-Grossberg neural networks (CGNN) with discrete and infinitely distributed delays.
With the help of stochastic analysis technology, the Lyapunov-Krasovskii functional method, linear matrix inequalities technique (LMI), and the average dwell time approach (ADT), some novel sufficient conditions regarding the issues of mean-square uniformly ultimate boundedness, the existence of a stochastic attractor, and the mean-square exponential stability for the switched Cohen-Grossberg neural networks are established.
Finally, illustrative examples and their simulations are provided to illustrate the effectiveness of the proposed results.
American Psychological Association (APA)
Huang, Chuangxia& Cao, Jie& Wang, Peng. 2016. Attractor and Boundedness of Switched Stochastic Cohen-Grossberg Neural Networks. Discrete Dynamics in Nature and Society،Vol. 2016, no. 2016, pp.1-19.
https://search.emarefa.net/detail/BIM-1103469
Modern Language Association (MLA)
Huang, Chuangxia…[et al.]. Attractor and Boundedness of Switched Stochastic Cohen-Grossberg Neural Networks. Discrete Dynamics in Nature and Society No. 2016 (2016), pp.1-19.
https://search.emarefa.net/detail/BIM-1103469
American Medical Association (AMA)
Huang, Chuangxia& Cao, Jie& Wang, Peng. Attractor and Boundedness of Switched Stochastic Cohen-Grossberg Neural Networks. Discrete Dynamics in Nature and Society. 2016. Vol. 2016, no. 2016, pp.1-19.
https://search.emarefa.net/detail/BIM-1103469
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1103469