Case study : an effect of noise in character recognition system using neural network

There has been resurgence of interest in artificial neural networks over the past few years, as a researchers from diverse backgrounds have produced a firms theoretical foundation and demonstrated numerous applications of this rich field of study. Neural networks are useful tools for solving many...

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Main Author:	Mohamad, Esmawaty
Format:	Thesis
Language:	English English
Published:	2003
Subjects:	Neural networks (Computer science) - Case studies Noise - Case studies
Online Access:	http://psasir.upm.edu.my/id/eprint/8706/1/FSKTM_2003_8%20IR.pdf
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id	my-upm-ir.8706
record_format	uketd_dc
spelling	my-upm-ir.87062023-12-28T01:21:21Z Case study : an effect of noise in character recognition system using neural network 2003-05 Mohamad, Esmawaty There has been resurgence of interest in artificial neural networks over the past few years, as a researchers from diverse backgrounds have produced a firms theoretical foundation and demonstrated numerous applications of this rich field of study. Neural networks are useful tools for solving many type of problems. These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. There has been great deal of work on enhancing neural network performance. Two important parameter are convergence and generalization. Convergence is the amount of time, measured in CPU operations or training epochs, required to find an acceptable solution for training. Generalization measures the ability to correctly classify new unseen data. This project studies the generalization ability of trained network to classify noisy data. The aim of this project is to develop a network that is able to recognize various inputs through a series of simulation using Neural Network simulator called MATLAB. The effect of the created network with noise are seen. This projects uses the most popular training method in character recognition problem, namely backpropagation algorithm. The theoretical foundation of this algorithm will be studied and summarized. Simulation experiment results on training and testing data will be recorded and discussed. Neural networks (Computer science) - Case studies Noise - Case studies 2003-05 Thesis http://psasir.upm.edu.my/id/eprint/8706/ http://psasir.upm.edu.my/id/eprint/8706/1/FSKTM_2003_8%20IR.pdf text en public masters Universiti Putra Malaysia Neural networks (Computer science) - Case studies Noise - Case studies Faculty of Computer Science and Information Technology Mohd Aris, Teh Noranis English
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English English
advisor	Mohd Aris, Teh Noranis
topic	Neural networks (Computer science) - Case studies Noise - Case studies
spellingShingle	Neural networks (Computer science) - Case studies Noise - Case studies Mohamad, Esmawaty Case study : an effect of noise in character recognition system using neural network
description	There has been resurgence of interest in artificial neural networks over the past few years, as a researchers from diverse backgrounds have produced a firms theoretical foundation and demonstrated numerous applications of this rich field of study. Neural networks are useful tools for solving many type of problems. These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. There has been great deal of work on enhancing neural network performance. Two important parameter are convergence and generalization. Convergence is the amount of time, measured in CPU operations or training epochs, required to find an acceptable solution for training. Generalization measures the ability to correctly classify new unseen data. This project studies the generalization ability of trained network to classify noisy data. The aim of this project is to develop a network that is able to recognize various inputs through a series of simulation using Neural Network simulator called MATLAB. The effect of the created network with noise are seen. This projects uses the most popular training method in character recognition problem, namely backpropagation algorithm. The theoretical foundation of this algorithm will be studied and summarized. Simulation experiment results on training and testing data will be recorded and discussed.
format	Thesis
qualification_level	Master's degree
author	Mohamad, Esmawaty
author_facet	Mohamad, Esmawaty
author_sort	Mohamad, Esmawaty
title	Case study : an effect of noise in character recognition system using neural network
title_short	Case study : an effect of noise in character recognition system using neural network
title_full	Case study : an effect of noise in character recognition system using neural network
title_fullStr	Case study : an effect of noise in character recognition system using neural network
title_full_unstemmed	Case study : an effect of noise in character recognition system using neural network
title_sort	case study : an effect of noise in character recognition system using neural network
granting_institution	Universiti Putra Malaysia
granting_department	Faculty of Computer Science and Information Technology
publishDate	2003
url	http://psasir.upm.edu.my/id/eprint/8706/1/FSKTM_2003_8%20IR.pdf
_version_	1794018774683222016

Case study : an effect of noise in character recognition system using neural network

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