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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| Pengarang-pengarang Utama: | , , |
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| Format: | Artikel |
| Diterbitkan: |
Asian Research Publishing Network (ARPN)
2015
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| Subjek-subjek: | |
| Capaian Atas Talian: | http://eprints.utm.my/55278/ |
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