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dc.contributor.authorGu, Yajuan
dc.contributor.authorWang, Hu
dc.contributor.authorYu, Yongguang
dc.date.accessioned2019-03-17T10:00:20Z
dc.date.available2019-03-17T10:00:20Z
dc.date.copyright2/15/2019 12:00:00 AM
dc.date.issued2019
dc.identifier.issn1555-1415
dc.identifier.othercnd_014_05_051002.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255852
dc.description.abstractSynchronization for incommensurate Riemann–Liouville fractional competitive neural networks (CNN) with different time scales is investigated in this paper. Time delays and unknown parameters are concerned in the model, which is more practical. Two simple and effective controllers are proposed, respectively, such that synchronization between the salve system and the master system with known or unknown parameters can be achieved. The methods are more general and less conservative which can also be applied to commensurate integer-order systems and commensurate fractional systems. Furthermore, two numerical ensamples are provided to show the feasibility of the approach. Based on the chaotic masking method, the example of chaos synchronization application for secure communication is provided.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleSynchronization for Incommensurate Riemann–Liouville Fractional-Order Time-Delayed Competitive Neural Networks With Different Time Scales and Known or Unknown Parameters1
dc.typeJournal Paper
dc.journal.volume14
dc.journal.issue5
dc.journal.titleJournal of Computational and Nonlinear Dynamics
dc.identifier.doi10.1115/1.4042494
dc.journal.fristpage51002
dc.journal.lastpage051002-9
dc.treeJournal of Computational and Nonlinear Dynamics:;2019:;volume( 014 ):;issue: 005
dc.contenttypeFulltext


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