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

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 Abstract: 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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 Dates: 2020
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: 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
 Degree: -

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Title: Neurocomputing
Source Genre: Journal, SCI, Scopus
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Publ. Info: -
Pages: - Volume / Issue: 401 Sequence Number: - Start / End Page: 364 - 376 Identifier: Other: Elsevier
Other: 1872-8286
ISSN: 0925-2312
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/neurocomputing
Publisher: Elsevier