Presentation 2011-09-21
A Study on Clustering for Anomalous Signal Detections from Electromagnetic Wave Data
Satoshi URATA, Hiroshi YASUKAWA, Akitoshi ITAI, Ichi TAKUMI,
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Abstract(in English) It is known that the detection of an anomalous signal radiated from the earth's crust is useful for predicting the precursor of the earthquakes. We have observed the electromagnetic (EM) wave using the Extremely Low Frequency band. Various methods for detection of an anomalous signal have been proposed. The known problem of those technique is related to a false detection due to the limitation of training data. We proposed the HMM based anomalous signal detection whose training data is the amplitude density distribution extracted from normal EM wave signals. However, the time resolution of anomalous signal detection is not discussed enough. In this paper, anomalous signal detection using amplitude density distribution calculated by short term signals is proposed to track a temporal change of acceptance probability.
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Keyword(in English) electromagnetic wave / Hidden Markov Model / extremely low frequency band / amplitude density distribution / signal detection
Paper # SIS2011-23
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Conference Date 2011/9/14(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
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Title (in English) A Study on Clustering for Anomalous Signal Detections from Electromagnetic Wave Data
Sub Title (in English)
Keyword(1) electromagnetic wave
Keyword(2) Hidden Markov Model
Keyword(3) extremely low frequency band
Keyword(4) amplitude density distribution
Keyword(5) signal detection
1st Author's Name Satoshi URATA
1st Author's Affiliation Graduate School of Information Science and Technology, Aichi Prefectural University()
2nd Author's Name Hiroshi YASUKAWA
2nd Author's Affiliation Graduate School of Information Science and Technology, Aichi Prefectural University
3rd Author's Name Akitoshi ITAI
3rd Author's Affiliation Collage of Engineering, Chubu University
4th Author's Name Ichi TAKUMI
4th Author's Affiliation Nagoya Institute of Technology
Date 2011-09-21
Paper # SIS2011-23
Volume (vol) vol.111
Number (no) 210
Page pp.pp.-
#Pages 6
Date of Issue