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Feature Extraction and Classification of EEG Spectra of Alcoholic Subjects
| National Symposium on Modern Information and Communication Technologies for Digital India |
| Foundation of Computer Science USA |
| MICTDI2016 - Number 1 |
| December 2016 |
| Authors: Paramita Guha, Sugandh Jain, Sunita Mishra |
| 10043b2e-e516-40ea-aa63-a38db7d25cb8 |
Paramita Guha, Sugandh Jain, Sunita Mishra . Feature Extraction and Classification of EEG Spectra of Alcoholic Subjects. National Symposium on Modern Information and Communication Technologies for Digital India. MICTDI2016, 1 (December 2016), 31-34.
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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