The effect of delays on the performance of Layer Recurrent Network

Layer 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 ex...

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Main Authors: Li T.C., Nordin F.H., Yap K.S.
Other Authors: 36470545400
Format: Conference paper
Published: 2023
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spelling my.uniten.dspace-306742023-12-29T15:51:11Z The effect of delays on the performance of Layer Recurrent Network Li T.C. Nordin F.H. Yap K.S. 36470545400 25930510500 24448864400 Delay Dynamic network Layer Recurrent Network (LRN) Information dissemination Network performance Delay Dynamic network Feed-back loop Input and outputs Non-linear model Numerical experiments Recurrent networks Signal processing Layer 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. Final 2023-12-29T07:51:11Z 2023-12-29T07:51:11Z 2010 Conference paper 10.1109/CSPA.2010.5545274 2-s2.0-77956534328 https://www.scopus.com/inward/record.uri?eid=2-s2.0-77956534328&doi=10.1109%2fCSPA.2010.5545274&partnerID=40&md5=e4e5bdc35fa103cf80ff38b6c12f35fc https://irepository.uniten.edu.my/handle/123456789/30674 5545274 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Delay
Dynamic network
Layer Recurrent Network (LRN)
Information dissemination
Network performance
Delay
Dynamic network
Feed-back loop
Input and outputs
Non-linear model
Numerical experiments
Recurrent networks
Signal processing
spellingShingle Delay
Dynamic network
Layer Recurrent Network (LRN)
Information dissemination
Network performance
Delay
Dynamic network
Feed-back loop
Input and outputs
Non-linear model
Numerical experiments
Recurrent networks
Signal processing
Li T.C.
Nordin F.H.
Yap K.S.
The effect of delays on the performance of Layer Recurrent Network
description Layer 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.
author2 36470545400
author_facet 36470545400
Li T.C.
Nordin F.H.
Yap K.S.
format Conference paper
author Li T.C.
Nordin F.H.
Yap K.S.
author_sort Li T.C.
title The effect of delays on the performance of Layer Recurrent Network
title_short The effect of delays on the performance of Layer Recurrent Network
title_full The effect of delays on the performance of Layer Recurrent Network
title_fullStr The effect of delays on the performance of Layer Recurrent Network
title_full_unstemmed The effect of delays on the performance of Layer Recurrent Network
title_sort effect of delays on the performance of layer recurrent network
publishDate 2023
_version_ 1806424425006891008
score 13.222552