Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor

The purpose of this project is to develope an organizing discipline by which neural network system can be designed for specific computations. Furthermore, it is also to recognize and make use of both the similarities and differences between well-established procedures and the newly proposed neural n...

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Main Authors:	Mohd. Sharif, Kamaruzzaman, Mohd. Nor, Khairul Nazmi
Format:	Thesis
Language:	English
Published:	1992
Subjects:	Pattern recognition systems
Online Access:	https://ir.uitm.edu.my/id/eprint/100749/1/100749.pdf
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id	my-uitm-ir.100749
record_format	uketd_dc
spelling	my-uitm-ir.1007492024-09-12T03:10:25Z Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor 1992 Mohd. Sharif, Kamaruzzaman Mohd. Nor, Khairul Nazmi Pattern recognition systems The purpose of this project is to develope an organizing discipline by which neural network system can be designed for specific computations. Furthermore, it is also to recognize and make use of both the similarities and differences between well-established procedures and the newly proposed neural network approaches. 1992 Thesis https://ir.uitm.edu.my/id/eprint/100749/ https://ir.uitm.edu.my/id/eprint/100749/1/100749.pdf text en public advanced_diploma Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
topic	Pattern recognition systems
spellingShingle	Pattern recognition systems Mohd. Sharif, Kamaruzzaman Mohd. Nor, Khairul Nazmi Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor
description	The purpose of this project is to develope an organizing discipline by which neural network system can be designed for specific computations. Furthermore, it is also to recognize and make use of both the similarities and differences between well-established procedures and the newly proposed neural network approaches.
format	Thesis
qualification_level	advanced_diploma
author	Mohd. Sharif, Kamaruzzaman Mohd. Nor, Khairul Nazmi
author_facet	Mohd. Sharif, Kamaruzzaman Mohd. Nor, Khairul Nazmi
author_sort	Mohd. Sharif, Kamaruzzaman
title	Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor
title_short	Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor
title_full	Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor
title_fullStr	Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor
title_full_unstemmed	Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor
title_sort	self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / kamaruzzaman mohd. sharif and khairul nazmi mohd. nor
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	1992
url	https://ir.uitm.edu.my/id/eprint/100749/1/100749.pdf
_version_	1811769090991194112

Self organizing nets for pattern recognition (unsupervised learning based on discovery of cluster structure) / Kamaruzzaman Mohd. Sharif and Khairul Nazmi Mohd. Nor

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