Wavelet-based denoising algorithm for EEG signals--using scale dependent threshold based on median / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1227-1229, 2009.
Article
in Chinese
| WPRIM
| ID: wpr-244656
ABSTRACT
We have brought forward a wavelet-based algorithm for electroencephalograph (EEG) signals--using scale dependent threshold based on median. In comparison with the universal threshold and Sure threshold, our proposed threshold, which is adaptive to the subband noise signals, preserves the noise free reconstruction property and takes lower risk than does the universal threshold; and our proposed threshold overcomes the drawback of Sure threshold. Evidently, the scale dependent threshold based on median is computationally simple and can obtain higher singal-to-noise ratio (SNR) it outperforms the universal threshold and Sure threshlold.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Algorithms
/
Signal Processing, Computer-Assisted
/
Artifacts
/
Electroencephalography
Type of study:
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2009
Type:
Article
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