Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control
| Autor: | Yiping Luo, Tianhu Yu, Leszek Rutkowski, Jinde Cao |
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| Rok vydání: | 2021 |
| Předmět: |
Time Factors
Artificial neural network Computer Networks and Communications Stability criterion Computer science Settling time Control (management) Interval (mathematics) Synchronization Computer Science Applications Domain (software engineering) Artificial Intelligence Control theory Synchronization (computer science) Neural Networks Computer Software |
| Zdroj: | IEEE transactions on neural networks and learning systems. 33(8) |
| ISSN: | 2162-2388 |
| Popis: | The finite-time synchronization problem is investigated for the master-slave complex-valued memristive neural networks in this article. A novel Lyapunov-function based finite-time stability criterion with impulsive effects is proposed and utilized to design the decentralized finite-time synchronization controller. Not only the settling time but also the attractive domain with respect to the impulsive gain and average impulsive interval, as well as initial values is derived according to the sufficient synchronization condition. Two examples are outlined to illustrate the validity of our hybrid control strategy. |
| Databáze: | OpenAIRE |
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