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A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks.
- Source :
-
Neural networks : the official journal of the International Neural Network Society [Neural Netw] 2020 Mar; Vol. 123, pp. 412-419. Date of Electronic Publication: 2020 Jan 07. - Publication Year :
- 2020
-
Abstract
- In this paper, we derive a new fixed-time stability theorem based on definite integral, variable substitution and some inequality techniques. The fixed-time stability criterion and the upper bound estimate formula for the settling time are different from those in the existing fixed-time stability theorems. Based on the new fixed-time stability theorem, the fixed-time synchronization of neural networks is investigated by designing feedback controller, and sufficient conditions are derived to guarantee the fixed-time synchronization of neural networks. To show the usability and superiority of the obtained theoretical results, we propose a secure communication scheme based on the fixed-time synchronization of neural networks. Numerical simulations illustrate that the new upper bound estimate formula for the settling time is much tighter than those in the existing fixed-time stability theorems. Moreover, the plaintext signals can be recovered according to the new fixed-time stability theorem, while the plaintext signals cannot be recovered according to the existing fixed-time stability theorems.<br /> (Copyright © 2020 Elsevier Ltd. All rights reserved.)
- Subjects :
- Feedback
Time Factors
Neural Networks, Computer
Subjects
Details
- Language :
- English
- ISSN :
- 1879-2782
- Volume :
- 123
- Database :
- MEDLINE
- Journal :
- Neural networks : the official journal of the International Neural Network Society
- Publication Type :
- Academic Journal
- Accession number :
- 31945620
- Full Text :
- https://doi.org/10.1016/j.neunet.2019.12.028