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The effect of delays on the performance of Layer Recurrent Network

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dc.citedby0
dc.contributor.authorLi T.C.en_US
dc.contributor.authorNordin F.H.en_US
dc.contributor.authorYap K.S.en_US
dc.contributor.authorid36470545400en_US
dc.contributor.authorid25930510500en_US
dc.contributor.authorid24448864400en_US
dc.date.accessioned2023-12-29T07:51:11Z
dc.date.available2023-12-29T07:51:11Z
dc.date.issued2010
dc.description.abstractLayer Recurrent Network (LRN) is a dynamic network that has a feedback loop as well as a delay for each layer of the network except for the last layer. The main objective for this research is to study the effect of delays on the performance of the LRN in identifying a nonlinear model. A numerical experiment of the nonlinear model is set up before a set of input and output data is collected. The collected data is then used to train the LRN. The numbers of delays at the feedback loop is manipulated and the effect of the network performance is observed where it shows that the network has the best performance when the number of delay is set to more than the default/original value (which is one). � 2010 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo5545274
dc.identifier.doi10.1109/CSPA.2010.5545274
dc.identifier.scopus2-s2.0-77956534328
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-77956534328&doi=10.1109%2fCSPA.2010.5545274&partnerID=40&md5=e4e5bdc35fa103cf80ff38b6c12f35fc
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30674
dc.sourceScopus
dc.sourcetitleProceedings - CSPA 2010: 2010 6th International Colloquium on Signal Processing and Its Applications
dc.subjectDelay
dc.subjectDynamic network
dc.subjectLayer Recurrent Network (LRN)
dc.subjectInformation dissemination
dc.subjectNetwork performance
dc.subjectDelay
dc.subjectDynamic network
dc.subjectFeed-back loop
dc.subjectInput and outputs
dc.subjectNon-linear model
dc.subjectNumerical experiments
dc.subjectRecurrent networks
dc.subjectSignal processing
dc.titleThe effect of delays on the performance of Layer Recurrent Networken_US
dc.typeConference paperen_US
dspace.entity.typePublication
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