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Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks
Author
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-06-09
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
This paper is concerned with antisynchronization in predefined time for two different chaotic neural networks.
Firstly, a predefined-time stability theorem based on Lyapunov function is proposed.
With the help of the definition of predefined time, it is convenient to establish a direct relationship between the tuning gain of the system and the fixed stabilization time.
Then, the antisynchronization is achieved between two different chaotic neural networks via active control Lyapunov function design.
The designed controller presents the practical advantage that the least upper bound for the settling time can be explicitly defined during the control design.
With the help of the designed controller, the antisynchronization errors converge within a predefined-time period.
Numerical simulations are presented in order to show the reliability of the proposed method.
American Psychological Association (APA)
Lin, Lixiong. 2020. Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1143751
Modern Language Association (MLA)
Lin, Lixiong. Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1143751
American Medical Association (AMA)
Lin, Lixiong. Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1143751
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143751