We developed a method using synchrosqueezed transforms (SST) and convolutional neural networks (CNN) to recognize seismic phases from earthquake waveforms. The attention mechanism has added within the CNN to improve the accuracy of seismic phase picking. This approach transforms the 1D seismic signals into a 2D time-frequency representation using a synchrosqueezed transform (SST). We use Stanford Earthquake Dataset (STEAD) to train the proposed method.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Seismic Phase Picking Using Synchrosqueezed Transform and Attention Mechanism


    Beteiligte:
    Chen, Zejie (Autor:in) / Du, Yao (Autor:in) / Liu, Qian (Autor:in)


    Erscheinungsdatum :

    11.10.2023


    Format / Umfang :

    3916562 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    A Method of Human Motion Postures Analysis Using Synchrosqueezed Wavelet Transform

    Man, Weishi / Zhu, Zongyao / Zhang, Zhiyu et al. | British Library Online Contents | 2017




    Horizon picking in 3D seismic data volumes

    Faraklioti, M. / Petrou, M. | British Library Online Contents | 2004


    Order picking method and mechanism

    THEOBALD DANIEL | Europäisches Patentamt | 2018

    Freier Zugriff