Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays
Joint Authors
Liu, Xiaoping
Chen, Bing
Zhang, Ziye
Lin, Chong
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper focuses on the finite-time synchronization analysis for complex-valued recurrent neural networks with time delays.
First, two kinds of common activation functions appearing in the existing references are combined together and more general assumptions are given.
To achieve our aim, a nonlinear delayed controller with two independent parameters different from the existing ones is provided, which leads to great difficulty.
To overcome it, a newly developed inequality is used.
Then, via Lyapunov function approach, some criteria are derived to guarantee the finite-time synchronization of the considered system, and the settling time for synchronization is also estimated.
Finally, two numerical simulations are given to support the effectiveness and advantages of the obtained results.
American Psychological Association (APA)
Zhang, Ziye& Liu, Xiaoping& Lin, Chong& Chen, Bing. 2018. Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays. Complexity،Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1136198
Modern Language Association (MLA)
Zhang, Ziye…[et al.]. Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays. Complexity No. 2018 (2018), pp.1-14.
https://search.emarefa.net/detail/BIM-1136198
American Medical Association (AMA)
Zhang, Ziye& Liu, Xiaoping& Lin, Chong& Chen, Bing. Finite-Time Synchronization for Complex-Valued Recurrent Neural Networks with Time Delays. Complexity. 2018. Vol. 2018, no. 2018, pp.1-14.
https://search.emarefa.net/detail/BIM-1136198
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1136198