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PCA and DWT with Resilient ANN based Organic Compounds Charts Recognition

by Rabah N. Farhan, Salah A. Aliesawi, Zahraa Z. Abdulkareem
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 88 - Number 1
Year of Publication: 2014
Authors: Rabah N. Farhan, Salah A. Aliesawi, Zahraa Z. Abdulkareem
10.5120/15316-3615

Rabah N. Farhan, Salah A. Aliesawi, Zahraa Z. Abdulkareem . PCA and DWT with Resilient ANN based Organic Compounds Charts Recognition. International Journal of Computer Applications. 88, 1 ( February 2014), 22-27. DOI=10.5120/15316-3615

@article{ 10.5120/15316-3615,
author = { Rabah N. Farhan, Salah A. Aliesawi, Zahraa Z. Abdulkareem },
title = { PCA and DWT with Resilient ANN based Organic Compounds Charts Recognition },
journal = { International Journal of Computer Applications },
issue_date = { February 2014 },
volume = { 88 },
number = { 1 },
month = { February },
year = { 2014 },
issn = { 0975-8887 },
pages = { 22-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume88/number1/15316-3615/ },
doi = { 10.5120/15316-3615 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:06:29.975026+05:30
%A Rabah N. Farhan
%A Salah A. Aliesawi
%A Zahraa Z. Abdulkareem
%T PCA and DWT with Resilient ANN based Organic Compounds Charts Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 88
%N 1
%P 22-27
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A supervised learning depending on the resilient propagation neural network (RPROP) procedure has been used to solve the problem of FTIR charts recognition of the organic materials by training features extracted from two methods; principal component analysis (PCA) and discrete wavelet transform (DWT). During the testing process, it was found that; the best results are obtained from features that obtained from the principal component analysis, which in turn achieve a higher accuracy rate as well as the lowest false positive rate (where it gets accuracy rate about 97. 22%, where the false positive rate about 2. 7 %), where DWT get an accuracy rate about 91. 6%, where the false positive rate about 8. 3 %.

References
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Index Terms

Computer Science
Information Sciences

Keywords

FTIR spectrum Discrete Wavelet Transform Principal Component Analysis Resilient Propagation Neural Network

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