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Compression and Comparison of ECG Signals using DWT and DWPT


Affiliations
1 Electronics and Instrumentation Department, FISAT, Angamaly, Ernakulam - 683577, Kerala, India
2 Applied Electronics and Instrumentation Department, ASIET, Kalady, Ernakulam - 683574, Kerala, India
 

The work here attempts to incorporate the power of frequency domain tools like wavelets and wavelet packets for aiding data compression using runlength encoding. An attempt is made here to compare between the performance of wavelets and wavelet packets for data compression. The DWT is performed in one level with sym8, the coefficients are threshold by hard rule and encoding is done by zero run length. In case of DWPT the best tree is selected from level 8 decomposition based on maximum energy content in them and out of that sub bands, best bands are selected based on SVD.

Keywords

DWPT, DWT, ECG, Runlength Encoding
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  • Compression and Comparison of ECG Signals using DWT and DWPT

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Authors

Beenu Riju
Electronics and Instrumentation Department, FISAT, Angamaly, Ernakulam - 683577, Kerala, India
P. Sreevidya
Electronics and Instrumentation Department, FISAT, Angamaly, Ernakulam - 683577, Kerala, India
K. Smitha
Applied Electronics and Instrumentation Department, ASIET, Kalady, Ernakulam - 683574, Kerala, India

Abstract


The work here attempts to incorporate the power of frequency domain tools like wavelets and wavelet packets for aiding data compression using runlength encoding. An attempt is made here to compare between the performance of wavelets and wavelet packets for data compression. The DWT is performed in one level with sym8, the coefficients are threshold by hard rule and encoding is done by zero run length. In case of DWPT the best tree is selected from level 8 decomposition based on maximum energy content in them and out of that sub bands, best bands are selected based on SVD.

Keywords


DWPT, DWT, ECG, Runlength Encoding



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i24%2F141620