Performance evaluation of radial basis function neural networks

The work was done to compare the performance of the radial basis function neural networks with that of back propagation neural networks. The comparison was made both in the field of function approximation and pattern recognition. Cosine function and the hermite's polynomial were used for functi...

Full description

Saved in:

Bibliographic Details
Main Author:	Arun Kumar.
Other Authors:	Saratchandran, Paramasivan
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/4223
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-4223
record_format	dspace
spelling	sg-ntu-dr.10356-42232023-07-04T16:05:57Z Performance evaluation of radial basis function neural networks Arun Kumar. Saratchandran, Paramasivan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems The work was done to compare the performance of the radial basis function neural networks with that of back propagation neural networks. The comparison was made both in the field of function approximation and pattern recognition. Cosine function and the hermite's polynomial were used for function approximation comparison. For pattern recognition problem, a set of twenty-six English alphabets and another set of ten numeric digits were used. The various comparison parameters taken into account included training time for the particular network and the average absolute output error in case of noisy input. For the case of the noisy input data, results for various levels of noise were studied. Master of Science (Computer Control and Automation) 2008-09-17T09:47:03Z 2008-09-17T09:47:03Z 1999 1999 Thesis http://hdl.handle.net/10356/4223 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 Arun Kumar. Performance evaluation of radial basis function neural networks
description	The work was done to compare the performance of the radial basis function neural networks with that of back propagation neural networks. The comparison was made both in the field of function approximation and pattern recognition. Cosine function and the hermite's polynomial were used for function approximation comparison. For pattern recognition problem, a set of twenty-six English alphabets and another set of ten numeric digits were used. The various comparison parameters taken into account included training time for the particular network and the average absolute output error in case of noisy input. For the case of the noisy input data, results for various levels of noise were studied.
author2	Saratchandran, Paramasivan
author_facet	Saratchandran, Paramasivan Arun Kumar.
format	Theses and Dissertations
author	Arun Kumar.
author_sort	Arun Kumar.
title	Performance evaluation of radial basis function neural networks
title_short	Performance evaluation of radial basis function neural networks
title_full	Performance evaluation of radial basis function neural networks
title_fullStr	Performance evaluation of radial basis function neural networks
title_full_unstemmed	Performance evaluation of radial basis function neural networks
title_sort	performance evaluation of radial basis function neural networks
publishDate	2008
url	http://hdl.handle.net/10356/4223
_version_	1772827213960314880

Performance evaluation of radial basis function neural networks

Similar Items