Training set parallel implementations and analysis of backpropagation neural networks in a transputer array

This thesis presents a detailed study of the parallel implementations of backpropagation neural networks for reducing the training time. There are mainly two paradigms in the parallel implementations, namely, network based parallelism and training set parallelism. This study emphasises training set...

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Main Author:	Foo, Shou King.
Other Authors:	Paramasivan Saratchandran
Format:	Theses and Dissertations
Language:	English
Published:	2009
Subjects:	DRNTU::Engineering::Electrical and electronic engineering
Online Access:	http://hdl.handle.net/10356/19761
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-19761
record_format	dspace
spelling	sg-ntu-dr.10356-197612023-07-04T15:45:55Z Training set parallel implementations and analysis of backpropagation neural networks in a transputer array Foo, Shou King. Paramasivan Saratchandran School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering This thesis presents a detailed study of the parallel implementations of backpropagation neural networks for reducing the training time. There are mainly two paradigms in the parallel implementations, namely, network based parallelism and training set parallelism. This study emphasises training set parallelism. Master of Engineering 2009-12-14T06:34:23Z 2009-12-14T06:34:23Z 1994 1994 Thesis http://hdl.handle.net/10356/19761 en NANYANG TECHNOLOGICAL UNIVERSITY 155 p. application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering Foo, Shou King. Training set parallel implementations and analysis of backpropagation neural networks in a transputer array
description	This thesis presents a detailed study of the parallel implementations of backpropagation neural networks for reducing the training time. There are mainly two paradigms in the parallel implementations, namely, network based parallelism and training set parallelism. This study emphasises training set parallelism.
author2	Paramasivan Saratchandran
author_facet	Paramasivan Saratchandran Foo, Shou King.
format	Theses and Dissertations
author	Foo, Shou King.
author_sort	Foo, Shou King.
title	Training set parallel implementations and analysis of backpropagation neural networks in a transputer array
title_short	Training set parallel implementations and analysis of backpropagation neural networks in a transputer array
title_full	Training set parallel implementations and analysis of backpropagation neural networks in a transputer array
title_fullStr	Training set parallel implementations and analysis of backpropagation neural networks in a transputer array
title_full_unstemmed	Training set parallel implementations and analysis of backpropagation neural networks in a transputer array
title_sort	training set parallel implementations and analysis of backpropagation neural networks in a transputer array
publishDate	2009
url	http://hdl.handle.net/10356/19761
_version_	1772826824731000832

Training set parallel implementations and analysis of backpropagation neural networks in a transputer array

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