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  IEEE Access Special Section Editorial: Recent Advances on Hybrid Complex Networks: Analysis and Control [Editorial]

Lu, J., Ho, D. W. C., Huang, T., Kurths, J., Trajkovic, L. (2021): IEEE Access Special Section Editorial: Recent Advances on Hybrid Complex Networks: Analysis and Control [Editorial]. - IEEE Access, 9, 95083-95086.
https://doi.org/10.1109/ACCESS.2021.3087971

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IEEE_Access_Special_Section_Editorial_Recent_Advances_on_Hybrid_Complex_Networks_Analysis_and_Control.pdf (Publisher version), 3MB
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 Creators:
Lu, Jianquan1, Author
Ho, Daniel W. C.1, Author
Huang, Tingwen1, Author
Kurths, Jürgen2, Author              
Trajkovic, Ljiljana1, Author
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Complex networks typically involve multiple disciplines due to network dynamics and their statistical nature. When modeling practical networks, both impulsive effects and logical dynamics have recently attracted increasing attention. Hence, it is of interest and importance to consider hybrid complex networks with impulsive effects and logical dynamics. Relevant research is prevalent in cells, ecology, social systems, and communication engineering. In hybrid complex networks, numerous nodes are coupled through networks and their properties usually lead to complex dynamic behaviors, including discrete and continuous dynamics with finite values of time and state space. Generally, continuous and discrete sections of the systems are described by differential and difference equations, respectively. Logical networks are used to model the systems where time and state space take finite values. Although interesting results have been reported regarding hybrid complex networks, the analysis methods and relevant results could be further improved with respect to conservative impulsive delay inequalities and reproducibility of corresponding stability or synchronization criteria. Therefore, it is necessary to devise effective approaches to improve the analysis method and results dealing with hybrid complex networks.

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 Dates: 2021-07
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1109/ACCESS.2021.3087971
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
MDB-ID: No data to archive
OATYPE: Gold Open Access
Research topic keyword: Complex Networks
Model / method: Machine Learning
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Title: IEEE Access
Source Genre: Journal, SCI, Scopus, p3
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Pages: - Volume / Issue: 9 Sequence Number: - Start / End Page: 95083 - 95086 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1803142
Publisher: Institute of Electrical and Electronics Engineers (IEEE)