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Feature Extraction and Classification of EEG Spectra of Alcoholic Subjects

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IJCA Proceedings on National Symposium on Modern Information and Communication Technologies for Digital India
© 2016 by IJCA Journal
MICTDI 2016 - Number 1
Year of Publication: 2016
Authors:
Paramita Guha
Sugandh Jain
Sunita Mishra

Paramita Guha, Sugandh Jain and Sunita Mishra. Article: Feature Extraction and Classification of EEG Spectra of Alcoholic Subjects. IJCA Proceedings on National Symposium on Modern Information and Communication Technologies for Digital India MICTDI 2016(1):31-34, December 2016. Full text available. BibTeX

@article{key:article,
	author = {Paramita Guha and Sugandh Jain and Sunita Mishra},
	title = {Article: Feature Extraction and Classification of EEG Spectra of Alcoholic Subjects},
	journal = {IJCA Proceedings on National Symposium on Modern Information and Communication Technologies for Digital India},
	year = {2016},
	volume = {MICTDI 2016},
	number = {1},
	pages = {31-34},
	month = {December},
	note = {Full text available}
}

Abstract

This paper considers the modeling and simulation techniques of electroencephalography (EEG) signals. EEG signals of two different categories of subjects viz. , alcoholic and normal patients are considered here. The signals are decomposed into several components using discrete wavelet transform technique to achieve different frequency bands of the brainwaves. After that different classification techniques, like, Principle Component Analysis (PCA) and Partial Least Square (PLS) to distinguish the alcoholic signals from the normal subjects. A comparative analysis is given and also further extensions are identified.

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