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Signal Extraction Problems in Seismology *
Author(s) -
Kitagawa Genshiro,
Takanami Tetsuo,
Matsumoto Norio
Publication year - 2001
Publication title -
international statistical review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.051
H-Index - 54
eISSN - 1751-5823
pISSN - 0306-7734
DOI - 10.1111/j.1751-5823.2001.tb00483.x
Subject(s) - extraction (chemistry) , seismic noise , geology , signal (programming language) , noise (video) , seismology , microseism , signal processing , remote sensing , computer science , telecommunications , artificial intelligence , chemistry , chromatography , image (mathematics) , programming language , radar
Summary The earth's surface is under continuous influence of a variety of natural forces such as the effect of past earthquakes, wave, wind, tide, air pressure, precipitation and a variety of human induced sources. Since it is almost impossible to describe the response to these noise inputs precisely, for automatic processing of seismic data, proper statistical modeling is necessary. In this paper, we describe four specific examples of time series modeling for signal extraction problems related to seismology. Namely, we consider 1) the estimation of the arrival time of a seismic signal, 2) the extraction of small seismic signal from noisy data, 3) the detection of the coseismic effect in groundwater level data contaminated by various effects from air pressure etc., and 4) the estimation of changing spectral characteristic of seismic record.