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contributor authorGu, Yajuan
contributor authorWang, Hu
contributor authorYu, Yongguang
date accessioned2019-03-17T10:00:20Z
date available2019-03-17T10:00:20Z
date copyright2/15/2019 12:00:00 AM
date issued2019
identifier issn1555-1415
identifier othercnd_014_05_051002.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4255852
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.
publisherThe American Society of Mechanical Engineers (ASME)
titleSynchronization for Incommensurate Riemann–Liouville Fractional-Order Time-Delayed Competitive Neural Networks With Different Time Scales and Known or Unknown Parameters1
typeJournal Paper
journal volume14
journal issue5
journal titleJournal of Computational and Nonlinear Dynamics
identifier doi10.1115/1.4042494
journal fristpage51002
journal lastpage051002-9
treeJournal of Computational and Nonlinear Dynamics:;2019:;volume( 014 ):;issue: 005
contenttypeFulltext


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