VHDL modelling of fixed-point DWT for the purpose of EMG signal denoising
Wavelet Transform (WT) has been widely applied in biomedical signal analysis. This paper will present the denoising method of EMG signal using WT and its model processed by VHSIC (Very High Speed Integrated Circuit) Hardware Description Language (VHDL) model of it. The principle of wavelet deno...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/6629/1/VHDL_Modelling_2011.pdf http://irep.iium.edu.my/6629/ http://dx.doi.org/10.1109/CICSyN.2011.58 |
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| Summary: | Wavelet Transform (WT) has been widely applied in
biomedical signal analysis. This paper will present the
denoising method of EMG signal using WT and its model
processed by VHSIC (Very High Speed Integrated Circuit)
Hardware Description Language (VHDL) model of it. The
principle of wavelet denoising is first to decompose the signal
by performing a WT, followed by applying suitable thresholds
to the detail coefficients, zeroing all coefficients below their
associated thresholds, and finally to reconstruct the denoised
signal based on the modified detail coefficients. Discrete
Wavelet Transform (DWT) is a method that uses wavelet
analyzer in which case the signal split into small pieces
preserving both time and frequency properties. The Second
order of Daubechies family (db2) has been used to denoise
EMG signals. The simulation, synthesis and verification of the
design presents a fast and reliable prototyping of DWT for
denoising of EMG signals. |
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