IEICE TRANSACTIONS on Fundamentals
A Study on Precursor Signal Extraction with PCA for Predicting Significant Earthquakes
Summary :
The tectonic activities that precede significant earthquakes release electromagnetic (EM) waves that can be used as earthquake precursors. We have been observing EM radiation in the ELF (extremely low frequency) band at about 40 observation stations in Japan for predicting significant earthquakes. The recorded signals contain, however, several noise components generated from the ionosphere, human activity, and so on. Most background noise in observed signal is attributed to lightning in the tropics. This paper proposes method based on PCA (principal component analysis) to extract signals from large data sets. The good performance of the proposed method is confirmed.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E86-A No.8 pp.2047-2052
- Publication Date
- 2003/08/01
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section on Digital Signal Processing)
- Category
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Shinji NIWA, Hiroshi YASUKAWA, Ichi TAKUMI, Masayasu HATA, "A Study on Precursor Signal Extraction with PCA for Predicting Significant Earthquakes" in IEICE TRANSACTIONS on Fundamentals,
vol. E86-A, no. 8, pp. 2047-2052, August 2003, doi: .
Abstract: The tectonic activities that precede significant earthquakes release electromagnetic (EM) waves that can be used as earthquake precursors. We have been observing EM radiation in the ELF (extremely low frequency) band at about 40 observation stations in Japan for predicting significant earthquakes. The recorded signals contain, however, several noise components generated from the ionosphere, human activity, and so on. Most background noise in observed signal is attributed to lightning in the tropics. This paper proposes method based on PCA (principal component analysis) to extract signals from large data sets. The good performance of the proposed method is confirmed.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e86-a_8_2047/_p
Copy
@ARTICLE{e86-a_8_2047,
author={Shinji NIWA, Hiroshi YASUKAWA, Ichi TAKUMI, Masayasu HATA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Study on Precursor Signal Extraction with PCA for Predicting Significant Earthquakes},
year={2003},
volume={E86-A},
number={8},
pages={2047-2052},
abstract={The tectonic activities that precede significant earthquakes release electromagnetic (EM) waves that can be used as earthquake precursors. We have been observing EM radiation in the ELF (extremely low frequency) band at about 40 observation stations in Japan for predicting significant earthquakes. The recorded signals contain, however, several noise components generated from the ionosphere, human activity, and so on. Most background noise in observed signal is attributed to lightning in the tropics. This paper proposes method based on PCA (principal component analysis) to extract signals from large data sets. The good performance of the proposed method is confirmed.},
keywords={},
doi={},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - A Study on Precursor Signal Extraction with PCA for Predicting Significant Earthquakes
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2047
EP - 2052
AU - Shinji NIWA
AU - Hiroshi YASUKAWA
AU - Ichi TAKUMI
AU - Masayasu HATA
PY - 2003
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E86-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2003
AB - The tectonic activities that precede significant earthquakes release electromagnetic (EM) waves that can be used as earthquake precursors. We have been observing EM radiation in the ELF (extremely low frequency) band at about 40 observation stations in Japan for predicting significant earthquakes. The recorded signals contain, however, several noise components generated from the ionosphere, human activity, and so on. Most background noise in observed signal is attributed to lightning in the tropics. This paper proposes method based on PCA (principal component analysis) to extract signals from large data sets. The good performance of the proposed method is confirmed.
ER -
English
