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  Synchronization of coupled memristive competitive BAM neural networks with different time scales

Zhao, Y., Ren, S., Kurths, J. (2021): Synchronization of coupled memristive competitive BAM neural networks with different time scales. - Neurocomputing, 427, 110-117.
https://doi.org/10.1016/j.neucom.2020.11.023

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 Creators:
Zhao, Yong1, Author
Ren, Shanshan1, Author
Kurths, Jürgen2, Author              
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: In this paper, synchronization of coupled memristive competitive bidirectional associative memory (BAM) neural networks with different time scales is discussed. Two kinds of feedback controllers are designed such that the response system and the drive system can reach synchronization. By using the differential inclusions theory, and constructing a proper Lyapunov–Krasovskii functional, novel sufficient conditions are obtained to achieve asymptotical synchronization of competitive BAM neural networks. The proposed synchronization can be easily realized. An illustrative example is given to show the feasibility of our theoretical results.

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 Dates: 2020-11-142020-11-282021-02-28
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1016/j.neucom.2020.11.023
MDB-ID: No data to archive
Research topic keyword: Complex Networks
Research topic keyword: Nonlinear Dynamics
Model / method: Machine Learning
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
 Degree: -

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Title: Neurocomputing
Source Genre: Journal, SCI, Scopus
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Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 427 Sequence Number: - Start / End Page: 110 - 117 Identifier: Publisher: Elsevier
Other: 1872-8286
ISSN: 0925-2312
CoNE: https://publications.pik-potsdam.de/cone/journals/resource/neurocomputing