IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v10y2022i22p4278-d973781.html
   My bibliography  Save this article

Two-Dimensional Correlation Analysis of Periodicity in Noisy Series: Case of VLF Signal Amplitude Variations in the Time Vicinity of an Earthquake

Author

Listed:
  • Andjelka B. Kovačević

    (Department of Astronomy, Faculty of Mathematics, University of Belgrade, Studentski trg 16, 11000 Belgrade, Serbia
    Key Laboratory for Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, 19B Yuquan Road, Beijing 100049, China)

  • Aleksandra Nina

    (Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia)

  • Luka Č. Popović

    (Department of Astronomy, Faculty of Mathematics, University of Belgrade, Studentski trg 16, 11000 Belgrade, Serbia
    Key Laboratory for Particle Astrophysics, Institute of High Energy Physics, Chinese Academy of Sciences, 19B Yuquan Road, Beijing 100049, China
    Astronomical Observatory, Volgina 7, 11160 Belgrade, Serbia)

  • Milan Radovanović

    (Geographical Institute Jovan Cvijić SASA, 11000 Belgrade, Serbia
    Institute of Sports, Tourism and Service, South Ural State University, 454080 Chelyabinsk, Russia)

Abstract

Extraction of information in the form of oscillations from noisy data of natural phenomena such as sounds, earthquakes, ionospheric and brain activity, and various emissions from cosmic objects is extremely difficult. As a method for finding periodicity in such challenging data sets, the 2D Hybrid approach, which employs wavelets, is presented. Our technique produces a wavelet transform correlation intensity contour map for two (or one) time series on a period plane defined by two independent period axes. Notably, by spreading peaks across the second dimension, our method improves the apparent resolution of detected oscillations in the period plane and identifies the direction of signal changes using correlation coefficients. We demonstrate the performance of the 2D Hybrid technique on a very low frequency (VLF) signal emitted in Italy and recorded in Serbia in time vicinity of the occurrence of an earthquake on 3 November 2010, near Kraljevo, Serbia. We identified a distinct signal in the range of 120–130 s that appears only in association with the considered earthquake. Other wavelets, such as Superlets, which may detect fast transient oscillations, will be employed in future analysis.

Suggested Citation

  • Andjelka B. Kovačević & Aleksandra Nina & Luka Č. Popović & Milan Radovanović, 2022. "Two-Dimensional Correlation Analysis of Periodicity in Noisy Series: Case of VLF Signal Amplitude Variations in the Time Vicinity of an Earthquake," Mathematics, MDPI, vol. 10(22), pages 1-14, November.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4278-:d:973781
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/10/22/4278/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/10/22/4278/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Vasile V. Moca & Harald Bârzan & Adriana Nagy-Dăbâcan & Raul C. Mureșan, 2021. "Time-frequency super-resolution with superlets," Nature Communications, Nature, vol. 12(1), pages 1-18, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yu, Qiang, 2023. "A homotopy-based wavelet method for extreme large bending analysis of heterogeneous anisotropic plate with variable thickness on orthotropic foundation," Applied Mathematics and Computation, Elsevier, vol. 439(C).
    2. Woojoong Kim & Munsu Lee & Sang-Jun Park & Sung-Hyun Jang & Byeong-Su Kang & Namjin Kim & Young-Sun Hong, 2022. "An Early Fault Diagnosis Method for Ball Bearings of Electric Vehicles Based on Integrated Subband Averaging and Enhanced Kurtogram Method," Energies, MDPI, vol. 15(15), pages 1-13, July.
    3. Johan Liljefors & Rita Almeida & Gustaf Rane & Johan N. Lundström & Pawel Herman & Mikael Lundqvist, 2024. "Distinct functions for beta and alpha bursts in gating of human working memory," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
    4. Haoxin Zhang & Ivan Skelin & Shiting Ma & Michelle Paff & Lilit Mnatsakanyan & Michael A. Yassa & Robert T. Knight & Jack J. Lin, 2024. "Awake ripples enhance emotional memory encoding in the human brain," Nature Communications, Nature, vol. 15(1), pages 1-13, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:10:y:2022:i:22:p:4278-:d:973781. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.