Cover Image

Identification of nonlinear systems using parallel Laguerre-NN model

In this paper, a nonlinear system identification framework using parallel linear-plus-neural networks model is developed. The framework is established by combining a linear Laguerre filter model and a nonlinear neural networks (NN) model in a parallel structure. The main advantage of the proposed pa...

Full description

Saved in:
Bibliographic Details
Main Authors: Zabiri, H., Ramasamy, M., Lemma, T.D., Maulud, A.
Format: Article
Published: 2013
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886245319&doi=10.4028%2fwww.scientific.net%2fAMR.785-786.1430&partnerID=40&md5=f400621f55680ac92ae44b6c1b385471
http://eprints.utp.edu.my/32731/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.32731
record_format eprints
spelling my.utp.eprints.327312022-03-30T01:05:04Z Identification of nonlinear systems using parallel Laguerre-NN model Zabiri, H. Ramasamy, M. Lemma, T.D. Maulud, A. In this paper, a nonlinear system identification framework using parallel linear-plus-neural networks model is developed. The framework is established by combining a linear Laguerre filter model and a nonlinear neural networks (NN) model in a parallel structure. The main advantage of the proposed parallel model is that by having a linear model as the backbone of the overall structure, reasonable models will always be obtained. In addition, such structure provides great potential for further study on extrapolation benefits and control. Similar performance of proposed method with other conventional nonlinear models has been observed and reported, indicating the effectiveness of the proposed model in identifying nonlinear systems. © (2013) Trans Tech Publications, Switzerland. 2013 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886245319&doi=10.4028%2fwww.scientific.net%2fAMR.785-786.1430&partnerID=40&md5=f400621f55680ac92ae44b6c1b385471 Zabiri, H. and Ramasamy, M. and Lemma, T.D. and Maulud, A. (2013) Identification of nonlinear systems using parallel Laguerre-NN model. Advanced Materials Research, 785-78 . pp. 1430-1436. http://eprints.utp.edu.my/32731/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description In this paper, a nonlinear system identification framework using parallel linear-plus-neural networks model is developed. The framework is established by combining a linear Laguerre filter model and a nonlinear neural networks (NN) model in a parallel structure. The main advantage of the proposed parallel model is that by having a linear model as the backbone of the overall structure, reasonable models will always be obtained. In addition, such structure provides great potential for further study on extrapolation benefits and control. Similar performance of proposed method with other conventional nonlinear models has been observed and reported, indicating the effectiveness of the proposed model in identifying nonlinear systems. © (2013) Trans Tech Publications, Switzerland.
format Article
author Zabiri, H.
Ramasamy, M.
Lemma, T.D.
Maulud, A.
spellingShingle Zabiri, H.
Ramasamy, M.
Lemma, T.D.
Maulud, A.
Identification of nonlinear systems using parallel Laguerre-NN model
author_facet Zabiri, H.
Ramasamy, M.
Lemma, T.D.
Maulud, A.
author_sort Zabiri, H.
title Identification of nonlinear systems using parallel Laguerre-NN model
title_short Identification of nonlinear systems using parallel Laguerre-NN model
title_full Identification of nonlinear systems using parallel Laguerre-NN model
title_fullStr Identification of nonlinear systems using parallel Laguerre-NN model
title_full_unstemmed Identification of nonlinear systems using parallel Laguerre-NN model
title_sort identification of nonlinear systems using parallel laguerre-nn model
publishDate 2013
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886245319&doi=10.4028%2fwww.scientific.net%2fAMR.785-786.1430&partnerID=40&md5=f400621f55680ac92ae44b6c1b385471
http://eprints.utp.edu.my/32731/
_version_ 1738657427864158208
score 13.18916

Similar Items