Bulletin KRASEC. Phys. & Math. Sci, 2015, V. 11, №. 2, pp. 73-78. ISSN 2313-0156

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DOI: 10.18454/2313-0156-2015-11-2-73-78

INFORMATION AND COMPUTATION TECHNOLOGIES

MSC 65D15

DENOISING OF GEOACOUSTIC EMISSION SIGNALS FROM NATURAL AND INDUSTRIAL NOISES USING SPARSE APPROXIMATION METHOD

O.O. Lukovenkova¹²

¹Institute of Cosmophysical Research and Radio Wave Propagation Far-Eastern Branch, Russian Academy of Sciences, 684034, Kamchatskiy Kray, Paratunka, Mirnaya st., 7, Russia.
²Kamchatka State University by Vitus Bering, 683032, Petropavlovsk-Kamchatskiy, Pogranichnaya st., 4, Russia.

E-mail: o.o.lukovenkova@yandex.ru

The paper suggests a method of denoising of geoacoustic emission signals from natural and industrial noises based on sparse approximation method. The method allowed the authors to clear geoacoustic emission pulses from spurious components.

Key words: sparse approximation, geoacoustic emission, matching pursuit, denoising.

References

  1. Marapulets Yu.V., Shevtsov B.M. Mezomasshtabnaya akusticheskaya emissiya [Mesoscale acoustic emission]. Vladivostok, Dal’nauka, 2012.
    2. Lukovenkova O.O. Comparison of sparse approximation methods based on its use to geoacoustic emission signals. Bulletin KRASEC. Phys. & Math. Sci., 2014, vol. 9, no. 2. pp. 70-78.
    3. Kim A.A. The use of parallel programming methods for time-frequency analysis of geoacoustic emission signals. Bulletin KRASEC. Phys. & Math. Sci., 2014. vol. 9, no. 2. pp. 62-69.
    4. Afanas’eva A.A., Lukovenkova O.O. Metody obnaruzheniya impul’sov geoakusticheskoi emissii na osnove algoritmov razrezhennoi approksimatsii i klasterizatsii [Methods for detection of geoactoustic emission pulses on the basis of sparse approximation algorithms and clasterization] Vestnik KRAUNTS — Bulletin KRASEC. Phys. & Math. Sci., 2013, No. 2 (7). pp. 68-73.
    5. Lukovenkova O.O., Tristanov A.B. Adaptivnyi algoritm soglasovannogo presledovaniya s utochneniem na smeshannykh slovaryakh v analize signalov geoakusticheskoi emissii [Adaptive algorithm of matching pursuit with a refinement on mixed dictionaries in the analysis of geoacoustic emission signals]. Tsifrovaya obrabotka signalov — Digital signal processing, 2014. No. 2, pp. 54-57.

For citation: Lukovenkova O.O. Denoising of geoacoustic emission signals from natural and industrial noises using sparse approximation method. Bulletin KRASEC. Physical and Mathematical Sciences 2015, vol. 11, issue 2, 73-78. DOI: 10.18454/2313-0156-2015-11-2-73-78.

Original article submitted: 03.11.2015

Luk

 

    Lukovenkova Olga Olegovna – Assistent of Dept. Informatics, Vitus Bering Kamchatka State University, Junior Researcher of Lab. Acoustic Research, Institute of Cosmophysical Research and Radio Wave Propagation FEB RAS.

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