Nonlinear system identification using integrated linear-NN models: series vs. parallel structures

Nonlinear system identification using integrated linear-NN models: series vs. parallel structures

In this paper, the performance of integrated linear-NN models is investigated for nonlinear system identification using two different structures: series vs. parallel. In particular, Laguerre filters are selected as the linear models, and multi-layer perceptron (MLP) or feed-forward neural networks...

Full description

Saved in:
Bibliographic Details
Main Authors: H., Zabiri, M., Ramasamy, Lemma D, Tufa, Maulud, Abdulhalim
Format: Conference or Workshop Item
Published: 2011
Subjects:
TP Chemical technology
Online Access:http://eprints.utp.edu.my/10747/1/7-ICMSC2011S021.pdf
http://www.ipcsit.com/vol10/7-ICMSC2011S021.pdf
http://eprints.utp.edu.my/10747/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Petronas
id my.utp.eprints.10747
record_format eprints
spelling my.utp.eprints.107472013-12-16T23:48:36Z Nonlinear system identification using integrated linear-NN models: series vs. parallel structures H., Zabiri M., Ramasamy Lemma D, Tufa Maulud, Abdulhalim TP Chemical technology In this paper, the performance of integrated linear-NN models is investigated for nonlinear system identification using two different structures: series vs. parallel. In particular, Laguerre filters are selected as the linear models, and multi-layer perceptron (MLP) or feed-forward neural networks (NN) are selected for the nonlinear models. Results show promising capability of the (novel) parallel Laguerre-NN structure especially in terms of its generalization capability when subjected to data different from those used during the identification stage in comparison to the series Laguerre-NN. 2011 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/10747/1/7-ICMSC2011S021.pdf http://www.ipcsit.com/vol10/7-ICMSC2011S021.pdf H., Zabiri and M., Ramasamy and Lemma D, Tufa and Maulud, Abdulhalim (2011) Nonlinear system identification using integrated linear-NN models: series vs. parallel structures. In: 2011 International Conference on Modeling, Simulation and Control (IPCSIT), 2-4 September 2013, Singapore. http://eprints.utp.edu.my/10747/
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/
topic TP Chemical technology
spellingShingle TP Chemical technology
H., Zabiri
M., Ramasamy
Lemma D, Tufa
Maulud, Abdulhalim
Nonlinear system identification using integrated linear-NN models: series vs. parallel structures
description In this paper, the performance of integrated linear-NN models is investigated for nonlinear system identification using two different structures: series vs. parallel. In particular, Laguerre filters are selected as the linear models, and multi-layer perceptron (MLP) or feed-forward neural networks (NN) are selected for the nonlinear models. Results show promising capability of the (novel) parallel Laguerre-NN structure especially in terms of its generalization capability when subjected to data different from those used during the identification stage in comparison to the series Laguerre-NN.
format Conference or Workshop Item
author H., Zabiri
M., Ramasamy
Lemma D, Tufa
Maulud, Abdulhalim
author_facet H., Zabiri
M., Ramasamy
Lemma D, Tufa
Maulud, Abdulhalim
author_sort H., Zabiri
title Nonlinear system identification using integrated linear-NN models: series vs. parallel structures
title_short Nonlinear system identification using integrated linear-NN models: series vs. parallel structures
title_full Nonlinear system identification using integrated linear-NN models: series vs. parallel structures
title_fullStr Nonlinear system identification using integrated linear-NN models: series vs. parallel structures
title_full_unstemmed Nonlinear system identification using integrated linear-NN models: series vs. parallel structures
title_sort nonlinear system identification using integrated linear-nn models: series vs. parallel structures
publishDate 2011
url http://eprints.utp.edu.my/10747/1/7-ICMSC2011S021.pdf
http://www.ipcsit.com/vol10/7-ICMSC2011S021.pdf
http://eprints.utp.edu.my/10747/
_version_ 1738655892167983104

Similar Items