EEG Feature Extraction Based on Wavelet Decomposition

Abstract:

Wavelet decomposition is a commonly used tool, signal analysis using the wavelet decomposition, can put the source according to their demand is decomposed into different frequency signals, so as to provide convenience for the feature extraction and identification in this paper, the EEG signals, using the theory of wavelet decomposition is calculated, look from the calculation results, the wavelet decomposition can be used for feature extraction of EEG signals as well.

• Periodical: Applied Mechanics and Materials (Volumes 496-500)
• Pages: 2023-2026
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.496-500.2023
• Online since: January 2014
• Authors: Jian Feng Hu, Zhen Dong Mu, Jing Hai Yin
• Keywords: EEG, Feature Extraction, Wavelet Decomposition

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