Reconstruction of EEG Signal Based on Compressed Sensing and Wavelet Transform

Shuang Liang; Lu Li

doi:10.4028/www.scientific.net/AMM.734.617

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 734Reconstruction of EEG Signal Based on Compressed...

Reconstruction of EEG Signal Based on Compressed Sensing and Wavelet Transform

Abstract:

This paper, both theoretically and numerically, investigates an effective reconstruction of EEG signal. An optimization model is presented, which unifies different sparse signals. The model is solved by employing the proximal algorithm. Based on the theoretical analysis, the simulation of EEG signal is performed. Sparse representation of EEG signal is got by the technique of wavelet transform and the signal denoising is also obtained. Then, by using compressed sensing, the EEG signal is reconstructed. Our results show that the reconstructed signal is in good agreement with the original signal and retains the leading characteristic.

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Periodical:

Applied Mechanics and Materials (Volume 734)

Pages:

617-620

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.734.617

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Online since:

February 2015

Authors:

Shuang Liang, Lu Li*

Keywords:

Compressed Sensing, EEG Signal, Proximal Algorithm, Sparse Representation, Wavelet Transform (WT)

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