Earth Gravity Tide Signal Decomposition Model Based on PCA and Geophysical Information Extraction

DOI

10.2991/ifeesm-15.2015.142How to use a DOI?

Keywords

Principal Component Analysis; the earth gravity tide signal; geophysical information; decomposition model

Abstract

Principal Component Analysis (PCA) is a main approach based on the second order statistics. It can remove the correlation between the signal components. PCA has been widely used in blind source separation and received attention because of its potential application in signal processing. PCA’s principle algorithm, its simulation steps and its application in the earth gravity tide signal are introduced. The decomposition model can help us to analyze the geophysical information in signal. The result shows that PCA is a potential method in the earth gravity tide signal. So we can extract useful geophysical information from it to understand the interior structure of the earth and earthquake precursors.

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  - Dong-jun Zhong
AU  - Hai-yan Quan
PY  - 2015/09
DA  - 2015/09
TI  - Earth Gravity Tide Signal Decomposition Model Based on PCA and Geophysical Information Extraction
BT  - Proceedings of the 2015 International Forum on Energy, Environment Science and Materials
PB  - Atlantis Press
SP  - 762
EP  - 769
SN  - 2352-5401
UR  - https://doi.org/10.2991/ifeesm-15.2015.142
DO  - 10.2991/ifeesm-15.2015.142
ID  - Zhong2015/09
ER  -