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  Fixed-time synchronization of fractional order memristive MAM neural networks by sliding mode control

Wang, W., Jia, X., Wang, Z., Luo, X., Li, L., Kurths, J., Yuan, M. (2020): Fixed-time synchronization of fractional order memristive MAM neural networks by sliding mode control. - Neurocomputing, 401, 364-376.
https://doi.org/10.1016/j.neucom.2020.03.043

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Wang, Weiping1, Autor
Jia, Xiao1, Autor
Wang, Zhen1, Autor
Luo, Xiong1, Autor
Li, Lixiang1, Autor
Kurths, Jürgen2, Autor              
Yuan, Manman1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Zusammenfassung: In this paper, we first established the fractional order memristive multidirectional associative memory neural networks (FMMAMNNs) model, and then considered its fixed-time synchronization control problem. On the basis of sliding model control and Lyapunov stability theorem, a fractional order sliding mode controller is constructed. By adding this controller to the response system, the error of the driver-response systems gradually converges to 0 in a fixed time. Compared with the previous researches, this paper considers a more complex model, and the proposed control theories can ensure that the setting time is only related to the model and controller, but not to the initial states of the system. Besides, the control theories are also applicable to the integer order models. Finally, two numerical simulations are given, the results show the validity of the theories.

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 Datum: 2020
 Publikationsstatus: Final veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.neucom.2020.03.043
PIKDOMAIN: RD4 - Complexity Science
MDB-ID: No data to archive
Working Group: Network- and machine-learning-based prediction of extreme events
 Art des Abschluß: -

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Titel: Neurocomputing
Genre der Quelle: Zeitschrift, SCI, Scopus
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 401 Artikelnummer: - Start- / Endseite: 364 - 376 Identifikator: Anderer: Elsevier
Anderer: 1872-8286
ISSN: 0925-2312
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/neurocomputing
Publisher: Elsevier