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Fuzzy rule based multiwavelet ECG signal denoising

By Wing-Kuen Ling, Yuk-Fan Ho, Hak-Keung Lam, Pak-Lin Wong, Yick-Po Chan and Kwong-Shun Tam

Abstract

Since different multiwavelets, pre- and post-filters have different impulse responses and frequency responses, different multiwavelets, pre- and post-filters should be selected and applied at different noise levels for signal denoising if signals are corrupted by additive white Gaussian noises. In this paper, some fuzzy rules are formulated for integrating different multiwavelets, pre- and post-filters together so that expert knowledge on employing different multiwavelets, pre- and post-filters at different noise levels on denoising performances is exploited. When an ECG signal is received, the noise level is first estimated. Then, based on the estimated noise level and our proposed fuzzy rules, different multiwavelets, pre- and post-filters are integrated together. A hard thresholding is applied on the multiwavelet coefficients. According to extensive numerical computer simulations, our proposed fuzzy rule based multiwavelet denoising algorithm outperforms traditional multiwavelet denoising algorithms by 30%

Topics: H610 Electronic Engineering
Publisher: IEEE
Year: 2008
DOI identifier: 10.1109/FUZZY.2008.4630501
OAI identifier: oai:eprints.lincoln.ac.uk:3125

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Citations

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