Szczegóły publikacji
Opis bibliograficzny
Finite-time synchronization of complex-valued memristive-based neural networks via hybrid control / Tianhu Yu, Jinde Cao, Leszek Rutkowski, Yi-Ping Luo // IEEE Transactions on Neural Networks and Learning Systems ; ISSN 2162-237X. — 2022 — vol. 33 no. 8, s. 3938–3947. — Bibliogr. s. 3946–3947, Abstr. — L. Rutkowski - afiliacja: Institute of Computational Intelligence, Czestochowa University of Technology, Czestochowa, Poland; Information Technology Institute, University of Social Sciences, Łódź, Poland
Autorzy (4)
- Yu Tianhu
- Cao JinDe
- Rutkowski Leszek
- Luo Yiping
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 144541 |
|---|---|
| Data dodania do BaDAP | 2023-01-12 |
| Tekst źródłowy | URL |
| DOI | 10.1109/TNNLS.2021.3054967 |
| Rok publikacji | 2022 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | IEEE Transactions on Neural Networks and Learning Systems |
Abstract
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.