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Localization, Recognition, and Classification of a Superficial Seismic Source in an Inhomogeneous Mean

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Sensors and Microsystems

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 268))

Abstract

In this work, a method for localization, recognition, and classification of a superficial seismic source in a real geological medium is presented. Localization is based on the DOA (Direction of Arrival) and on RSSR (Received Signal Strength Ratio) algorithms applied after Love and Rayleigh superficial wave separation. Recognition and classification methods make use of PCA (Principal Component Analysis) and K-means algorithm. The efficiency of this method is illustrated with experimental results.

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Acknowledgments

We gratefully acknowledge the assistance and the encouragement of Prof. A. D’Amico (Department of Electronic Engineering, Tor Vergata University, Rome, Italy) during the preparation of this work and the technical support given by Mr. Luca Imperatori and Mr. Massimo Di Menno Di Bucchianico (CNR IDASC).

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Authors and Affiliations

  1. IDASC-CNR, Area della Ricerca di Roma Tor Vergata, Via Fosso del Cavaliere 100, Roma, 00133, Italy

    F. Lo Castro, M. De Luca & S. Iarossi

Authors
  1. F. Lo Castro
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  2. M. De Luca
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  3. S. Iarossi
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Corresponding author

Correspondence to F. Lo Castro .

Editor information

Editors and Affiliations

  1. Dept. of Electronic Engineering, University of Rome Tor Vergata, Rome, Italy

    Corrado Di Natale

  2. Department of Information Engineering, University of Brescia, Brescia, Italy

    Vittorio Ferrari

  3. SENSOR Laboratory, IDASC, National Research Council (CNR), Brescia, Italy

    Andrea Ponzoni

  4. Department of Information Engineering, University of Brescia, Brescia, Italy

    Giorgio Sberveglieri

  5. Department of Information Engineering, University of Brescia, Brescia, Italy

    Marco Ferrari

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Castro, F.L., De Luca, M., Iarossi, S. (2014). Localization, Recognition, and Classification of a Superficial Seismic Source in an Inhomogeneous Mean. In: Di Natale, C., Ferrari, V., Ponzoni, A., Sberveglieri, G., Ferrari, M. (eds) Sensors and Microsystems. Lecture Notes in Electrical Engineering, vol 268. Springer, Cham. https://doi.org/10.1007/978-3-319-00684-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-00684-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00683-3

  • Online ISBN: 978-3-319-00684-0

  • eBook Packages: EngineeringEngineering (R0)

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