Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29414


Select areas to restrict search in scientific publication database:
16666
Discrete Wavelet Transform Decomposition Level Determination Exploiting Sparseness Measurement
Abstract:
Discrete wavelet transform (DWT) has been widely adopted in biomedical signal processing for denoising, compression and so on. Choosing a suitable decomposition level (DL) in DWT is of paramount importance to its performance. In this paper, we propose to exploit sparseness of the transformed signals to determine the appropriate DL. Simulation results have shown that the sparseness of transformed signals after DWT increases with the increasing DLs. Additional Monte-Carlo simulation results have verified the effectiveness of sparseness measure in determining the DL.
Digital Object Identifier (DOI):

References:


[1]S. K. Mitra, Digital Signal Processing: A Computer Based Approach. McGraw-Hill, 2005.
[2] S. S. Patil and M. K. Pawar, “Quality advancement of EEG by wavelet denoising for biomedical analysis,” in Proc. Int. Conf. on Communication, Information and Computing Technology, Oct. 2012.
[3] X. Liu, Y. J. Zheng, M. W. Phyu, B. Zhao, and X. J. Yuan, “Power & area efficient wavelet-based on-chip ECG processor for WBAN,” in Proc. IEEE Int. Conf. on Body Sensor Networks, 2010, pp. 124–130.
[4] P. Karthikeyan, M. Murugappan, and S.Yaacob, “ECG signal denoising using wavelet thresholding techniques in human stress assessment,” International Journal on Electrical Engineering and Informatics, vol. 4, no. 2, Jul. 2012.
[5] Z. Zhao and P. Min, “ECG denoising by sparse wavelet shrinkage,” in Proc. IEEE Conf. Bioinformatics and Biomedical Engineering, 2007, pp. 786–789.
[6] X. Liu, Y. J. Zheng, M. W. Phyu, B. Zhao, M.-K. Y. Je, and X. J. Yuan, “Multiple functional ECG signal is processing for wearable applications for long-term cardiac monitoring,” IEEE Trans. Biomedical Engineering, vol. 58, pp. 380–389, 2011.
[7] R. Cohen, “Signal denoising using wavelets,” Technion, Israel Institute of Technology, Tech. Rep., 2011.
[8] D. Donoho, “De-noising by soft-thresholding,” IEEE Trans. Information Theory, vol. 41, pp. 613–627, 1995.
[9] Y. H. Peng, “De-noising by modified soft-thresholding,” in Proc. IEEE Asia-Pacific Conf. Circuits and Systems, 2000, pp. 760–762.
[10] D. W. Yan-Fang Sang and J.-C. Wu, “Entropy-based method of choosing the decomposition level in wavelet threshold de-noising,” Journal of Entropy and Information Studies, Jun. 2010.
[11] J. S. M. D. C. Robertson, O. I. Camps and W. B. Gish, “Wavelets and electromagnetic power system transient,” IEEE Trans. Power Delivery, vol. 11-2, pp. 1050–1058, Apr. 1996.
[12] A. M. R. Dixon, G. Allstot, D. Gangopadhyay, and D. J. Allstot, “Compressed sensing system considerations for ECG and EMG wireless biosensors,” IEEE Trans. Biomedical Circuits and Systems, vol. 6, no. 2, pp. 155–166, Apr. 2012.
[13] Online Available: http://gerstner.felk.cvut.cz/biolab/newbiolab/teach /mitdat.htm

Vol:13 No:03 2019Vol:13 No:02 2019Vol:13 No:01 2019
Vol:12 No:12 2018Vol:12 No:11 2018Vol:12 No:10 2018Vol:12 No:09 2018Vol:12 No:08 2018Vol:12 No:07 2018Vol:12 No:06 2018Vol:12 No:05 2018Vol:12 No:04 2018Vol:12 No:03 2018Vol:12 No:02 2018Vol:12 No:01 2018
Vol:11 No:12 2017Vol:11 No:11 2017Vol:11 No:10 2017Vol:11 No:09 2017Vol:11 No:08 2017Vol:11 No:07 2017Vol:11 No:06 2017Vol:11 No:05 2017Vol:11 No:04 2017Vol:11 No:03 2017Vol:11 No:02 2017Vol:11 No:01 2017
Vol:10 No:12 2016Vol:10 No:11 2016Vol:10 No:10 2016Vol:10 No:09 2016Vol:10 No:08 2016Vol:10 No:07 2016Vol:10 No:06 2016Vol:10 No:05 2016Vol:10 No:04 2016Vol:10 No:03 2016Vol:10 No:02 2016Vol:10 No:01 2016
Vol:9 No:12 2015Vol:9 No:11 2015Vol:9 No:10 2015Vol:9 No:09 2015Vol:9 No:08 2015Vol:9 No:07 2015Vol:9 No:06 2015Vol:9 No:05 2015Vol:9 No:04 2015Vol:9 No:03 2015Vol:9 No:02 2015Vol:9 No:01 2015
Vol:8 No:12 2014Vol:8 No:11 2014Vol:8 No:10 2014Vol:8 No:09 2014Vol:8 No:08 2014Vol:8 No:07 2014Vol:8 No:06 2014Vol:8 No:05 2014Vol:8 No:04 2014Vol:8 No:03 2014Vol:8 No:02 2014Vol:8 No:01 2014
Vol:7 No:12 2013Vol:7 No:11 2013Vol:7 No:10 2013Vol:7 No:09 2013Vol:7 No:08 2013Vol:7 No:07 2013Vol:7 No:06 2013Vol:7 No:05 2013Vol:7 No:04 2013Vol:7 No:03 2013Vol:7 No:02 2013Vol:7 No:01 2013
Vol:6 No:12 2012Vol:6 No:11 2012Vol:6 No:10 2012Vol:6 No:09 2012Vol:6 No:08 2012Vol:6 No:07 2012Vol:6 No:06 2012Vol:6 No:05 2012Vol:6 No:04 2012Vol:6 No:03 2012Vol:6 No:02 2012Vol:6 No:01 2012
Vol:5 No:12 2011Vol:5 No:11 2011Vol:5 No:10 2011Vol:5 No:09 2011Vol:5 No:08 2011Vol:5 No:07 2011Vol:5 No:06 2011Vol:5 No:05 2011Vol:5 No:04 2011Vol:5 No:03 2011Vol:5 No:02 2011Vol:5 No:01 2011
Vol:4 No:12 2010Vol:4 No:11 2010Vol:4 No:10 2010Vol:4 No:09 2010Vol:4 No:08 2010Vol:4 No:07 2010Vol:4 No:06 2010Vol:4 No:05 2010Vol:4 No:04 2010Vol:4 No:03 2010Vol:4 No:02 2010Vol:4 No:01 2010
Vol:3 No:12 2009Vol:3 No:11 2009Vol:3 No:10 2009Vol:3 No:09 2009Vol:3 No:08 2009Vol:3 No:07 2009Vol:3 No:06 2009Vol:3 No:05 2009Vol:3 No:04 2009Vol:3 No:03 2009Vol:3 No:02 2009Vol:3 No:01 2009
Vol:2 No:12 2008Vol:2 No:11 2008Vol:2 No:10 2008Vol:2 No:09 2008Vol:2 No:08 2008Vol:2 No:07 2008Vol:2 No:06 2008Vol:2 No:05 2008Vol:2 No:04 2008Vol:2 No:03 2008Vol:2 No:02 2008Vol:2 No:01 2008
Vol:1 No:12 2007Vol:1 No:11 2007Vol:1 No:10 2007Vol:1 No:09 2007Vol:1 No:08 2007Vol:1 No:07 2007Vol:1 No:06 2007Vol:1 No:05 2007Vol:1 No:04 2007Vol:1 No:03 2007Vol:1 No:02 2007Vol:1 No:01 2007