In wavelet-based denoising of heart sounds, the decomposition level is the critical parameter for determining denoising quality.
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Prioritizing decomposition level may refine heart sound denoising; hypothesis-generating for parameter optimization in cardiovascular signal processing.
This paper focuses on the denoising of phonocardiogram (PCG) signals by means of discrete wavelet transform (DWT) using different wavelets and noise level estimation methods. The signal obtained by denoising from PCG signal contaminated white noise and the original PCG signal is compared to determine the appropriate parameters for denoising. The comparison is evaluated in terms of signal to noise ratio (SNR) before and after denoising. The results showed that the decomposition level is the most important parameter determining the denoising quality.
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Burhan Ergen (2013) studied this question.
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