Feature extraction of EEG signal using wavelet transform for autism classification

Feature extraction is a process to extract information from the electroencephalogram (EEG) signal to represent the large dataset before performing classification. This paper is intended to study the use of discrete wavelet transform (DWT) in extracting feature from EEG signal obtained by sensory res...

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Bibliographic Details
Main Authors: Lung, Chuin Cheong, Sudirman, Rubita, Hussin, Siti Suraya
Format: Article
Published: Asian Research Publishing Network (ARPN) 2015
Subjects: