Data classification using hybrid SOM-RBF architecture

Data classification using hybrid SOM-RBF architecture

This thesis looks into the methodologies of implementing hybrid neural network for data classification application. Among the vast varieties of Artificial Neural Network (ANN) architectures, each has its own unique capabilities. By proper combination of information from various specialised neural ne...

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Main Author: Choo, Chun Keong.
Other Authors: Suganthan, Ponnuthurai Nagaratnam
Format: Theses and Dissertations
Published: 2008
Subjects:
DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:http://hdl.handle.net/10356/4156
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Institution: Nanyang Technological University
id sg-ntu-dr.10356-4156
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spelling sg-ntu-dr.10356-41562023-07-04T15:12:35Z Data classification using hybrid SOM-RBF architecture Choo, Chun Keong. Suganthan, Ponnuthurai Nagaratnam School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems This thesis looks into the methodologies of implementing hybrid neural network for data classification application. Among the vast varieties of Artificial Neural Network (ANN) architectures, each has its own unique capabilities. By proper combination of information from various specialised neural networks of different paradigms. Master of Science (Computer Control and Automation) 2008-09-17T09:45:41Z 2008-09-17T09:45:41Z 2003 2003 Thesis http://hdl.handle.net/10356/4156 Nanyang Technological University application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
topic DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Choo, Chun Keong.
Data classification using hybrid SOM-RBF architecture
description This thesis looks into the methodologies of implementing hybrid neural network for data classification application. Among the vast varieties of Artificial Neural Network (ANN) architectures, each has its own unique capabilities. By proper combination of information from various specialised neural networks of different paradigms.
author2 Suganthan, Ponnuthurai Nagaratnam
author_facet Suganthan, Ponnuthurai Nagaratnam
Choo, Chun Keong.
format Theses and Dissertations
author Choo, Chun Keong.
author_sort Choo, Chun Keong.
title Data classification using hybrid SOM-RBF architecture
title_short Data classification using hybrid SOM-RBF architecture
title_full Data classification using hybrid SOM-RBF architecture
title_fullStr Data classification using hybrid SOM-RBF architecture
title_full_unstemmed Data classification using hybrid SOM-RBF architecture
title_sort data classification using hybrid som-rbf architecture
publishDate 2008
url http://hdl.handle.net/10356/4156
_version_ 1772827195012546560

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