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A Review on Different Techniques to De-noise a Signal
Author(s) -
Tanusree Ghosh,
Debnath Bhattacharyya,
Samir Kumar Bandyopadhyay,
Tai-hoon Kim
Publication year - 2014
Publication title -
international journal of control and automation
Language(s) - English
Resource type - Journals
eISSN - 2207-6387
pISSN - 2005-4297
DOI - 10.14257/ijca.2014.7.3.33
Subject(s) - noise (video) , computer science , signal (programming language) , acoustics , artificial intelligence , physics , image (mathematics) , programming language
This work is based on the comparative study of different decomposition methods used to de-noise an ECG signal. There are several signal processing techniques available like Fourier Transform method, Short Term Fourier Transform method, Wavelet analysis, Empirical Mode of Decomposition method etc. Though Fourier Transform method is predominantly used for decomposition purpose but it is not suitable for decomposition of nonstationary signal. However, most of the biomedical signals are non stationary in nature. So the signal should be decently de-noised thus it can provide essential clinical information relevant to patient’s health condition. The difficulties of FT method can be knocked out by Wavelet Transform method. As Wavelet Transform is a non adaptive approach, it is not satisfactory to eliminate the high frequency noise from signal. The complications of WT method can be diminished by Empirical Mode of Decomposition method. A detail study is required to find out the most advantageous decomposition method for an ECG signal.

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