Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

An Denoising Method Based on Analysis K-SVD and Disagreement Segment and Its Application on EMI Signal

Authors
Wen-Ru Gong, Hong-Yi Li, Di Zhao
Corresponding Author
Wen-Ru Gong
Available Online December 2016.
DOI
https://doi.org/10.2991/icwcsn-16.2017.75How to use a DOI?
Keywords
analysis K-SVD; EMI signal; disagreement-segment
Abstract
Sparse representation plays an important role in signal processing. Recently, the analysis sparse representation has been attracting more and more attention. In this paper, an improved analysis K-SVD denoising algorithm based on disagreement-segment is proposed. A signal is first divided into small redundant segments, and then the signal can be denoised by the analysis K-SVD algorithm. Considering the gap between the local processing and the global signal recovery, we define a disagreement-segment as the difference between the intermediate locally denoised segment and its corresponding part in the final denoised signal. By adding the disagreement-segment to the analysis K-SVD algorithm, the denoising effect of the analysis K-SVD algorithm has a significant improvement. In addition, the experimental results show that the proposed method outperforms the analysis K-SVD algorithm and other advanced methods.
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Proceedings
3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
Part of series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
978-94-6252-302-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icwcsn-16.2017.75How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wen-Ru Gong
AU  - Hong-Yi Li
AU  - Di Zhao
PY  - 2016/12
DA  - 2016/12
TI  - An Denoising Method Based on Analysis K-SVD and Disagreement Segment and Its Application on EMI Signal
BT  - 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.75
DO  - https://doi.org/10.2991/icwcsn-16.2017.75
ID  - Gong2016/12
ER  -