[Updated on Apr. 18] Integration of CiNii Articles into CiNii Research

Performance of Anomalous Signal Detection with HMM Approach in Electromagnetic Wave Observation Using Moving Window

  • ITO Yoshinao
    Graduate School of Information Science and Technology, Aichi Prefectural University
  • ITAI Akitoshi
    Graduate School of Information Science and Technology, Aichi Prefectural University
  • YASUKAWA Hiroshi
    Graduate School of Information Science and Technology, Aichi Prefectural University
  • TAKUMI Ichi
    Nagoya Institute of Technology
  • HATA Masayasu
    Collage of Engineering, Chubu University

Bibliographic Information

Other Title
  • 対数尤度の時間変動を考慮したHMMによるELF帯環境電磁波中の異常信号検出に関する性能評価
  • タイスウ ユウド ノ ジカン ヘンドウ オ コウリョ シタ HMM ニ ヨル ELFタイ カンキョウ デンジハ チュウ ノ イジョウ シンゴウ ケンシュツ ニ カンスル セイノウ ヒョウカ

Search this article

Abstract

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 observed the electromagnetic (EM) wave using the Extremely Low Frequency band. Various methods for detection of an anomalous signal have been proposed. Those methods have some problems. We proposed the anomalous signal detection based on HMM using the amplitude density distribution of an EM wave, which does not contain an anomalous signal. The input signals are calculated from the observed EM wave. An amplitude density distribution calculated from the image of an EM wave is employed as the input of HMM. In this paper, we evaluate the accuracy of an anomalous signal detection by using a temporal change of log likelihood calculated from EM wave data.

Journal

  • IEICE technical report

    IEICE technical report 110 (445), 77-81, 2011-02-24

    The Institute of Electronics, Information and Communication Engineers

Citations (1)*help

See more

References(20)*help

See more

Related Articles

See more

Related Data

See more

Related Books

See more

Related Dissertations

See more

Related Projects

See more

Related Products

See more

Details

Report a problem

Back to top