One Dimensional Signal Denoising Based on Wavelet Transform and Threshold Theory

DOI

10.2991/icefs-17.2017.54How to use a DOI?

Keywords

Wavelet analysis, De-noising, multiresolution analysis, Thresholding Value

Abstract

Wavelet analysis plays an important role in signal processing because of its good time-frequency locality and multi-resolution analysis performance. Based on wavelet analysis in one-dimensional signal denoising are studied, and the principle of threshold and threshold function of wavelet threshold denoising, the selection of wavelet base, decomposition layers and other related issues, and the relevant numerical experiments with Matlab software.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jinming Fu
AU  - Yuanfan Li
PY  - 2017/01
DA  - 2017/01
TI  - One Dimensional Signal Denoising Based on Wavelet Transform and Threshold Theory
BT  - Proceedings of the 2017 International Conference on Economics, Finance and Statistics (ICEFS 2017)
PB  - Atlantis Press
SP  - 420
EP  - 423
SN  - 2352-5428
UR  - https://doi.org/10.2991/icefs-17.2017.54
DO  - 10.2991/icefs-17.2017.54
ID  - Fu2017/01
ER  -