The study on denoising model of time series in big data

DOI

10.2991/isci-15.2015.96How to use a DOI?

Keywords

big data; windows Fourier transform; wavelet analysis; denoising; cluster

Abstract

A model which includes wavelet analysis and windows Fourier transform has been designed to resolve huge time series and interferential data in big data. In the model, the mass data firstly has been clustered as static or dynamic data. The static data has been processed by windows Fourier transform, and the dynamic data has been processed by wavelet analysis. After testing and simulation, the computing speed and denoising effect have been improved.

Copyright

© 2015, 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  - Xiaoming Guo
AU  - Xingwang Zhang
AU  - Jianming Cui
PY  - 2015/01
DA  - 2015/01
TI  - The study on denoising model of time series in big data
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 718
EP  - 725
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.96
DO  - 10.2991/isci-15.2015.96
ID  - Guo2015/01
ER  -