Alcoholic Brain State Identification from Brain Signals Using Support Vector Machine-Based Algorithm
Abstract
The paper aimed to present a method for the identification of alcoholic brain state using optimum allocation (OA)-based support vector machine (SVM). The OA scheme determines the representative data from a single time window of electroencephalogram (EEG) signals (called brain signal). Several statistical features have been extracted from each time window of EEG signals, and then these features are used to SVM classifier to identify the alcoholic...
Paper Details
Title
Alcoholic Brain State Identification from Brain Signals Using Support Vector Machine-Based Algorithm
Published Date
Jan 1, 2020
Pages
247 - 253
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