Predefined-Time Antisynchronization of Two Different Chaotic Neural Networks
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...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7476250 |
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| Summary: | 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. |
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| ISSN: | 1076-2787 1099-0526 |