A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems

67 p.

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Bibliographic Details
Main Author:	P. Karuppasami
Other Authors:	Narasimhan Sundararajan
Format:	Theses and Dissertations
Published:	2011
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Online Access:	http://hdl.handle.net/10356/46916
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Institution:	Nanyang Technological University

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spelling	sg-ntu-dr.10356-469162023-07-04T15:32:31Z A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems P. Karuppasami Narasimhan Sundararajan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems 67 p. This dissertation presents a Neural Network (NN) for multi-category classification problems and also presents the use of sequential learning algorithm, Extended Minimal Resource Allocating Network (EMRAN), to approximate the functional relationship between feature vector and class label. EMRAN uses Radial Basis Function (RBF) as its basic component. It has got growing and pruning strategy to find optimal hidden neurons. Its learning is based on Extended Kalman Filter (EKF) algorithm. In order to reduce the computational complexity, it updates only the winner neuron parameters. Master of Science (Computer Control and Automation) 2011-12-27T05:44:45Z 2011-12-27T05:44:45Z 2011 Thesis http://hdl.handle.net/10356/46916 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 P. Karuppasami A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems
description	67 p.
author2	Narasimhan Sundararajan
author_facet	Narasimhan Sundararajan P. Karuppasami
format	Theses and Dissertations
author	P. Karuppasami
author_sort	P. Karuppasami
title	A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems
title_short	A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems
title_full	A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems
title_fullStr	A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems
title_full_unstemmed	A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems
title_sort	study of extended minimal resource allocation network (emran) alogrithm for multi-category classification problems
publishDate	2011
url	http://hdl.handle.net/10356/46916
_version_	1772828835232874496

A study of extended minimal resource allocation network (EMRAN) alogrithm for multi-category classification problems

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