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A matched-filter technique with an objective threshold

We propose an objective threshold determination method for detecting outliers from the empirical distribution of cross-correlation coefficients among seismic waveforms. This method is aimed at detecting seismic signals from continuous waveform records. In our framework, detectability is automaticall...

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Detalles Bibliográficos
Autores principales: Hirano, Shiro, Kawakata, Hironori, Doi, Issei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9772383/
https://www.ncbi.nlm.nih.gov/pubmed/36543822
http://dx.doi.org/10.1038/s41598-022-25839-2
Descripción
Sumario:We propose an objective threshold determination method for detecting outliers from the empirical distribution of cross-correlation coefficients among seismic waveforms. This method is aimed at detecting seismic signals from continuous waveform records. In our framework, detectability is automatically determined from Akaike’s Information Criterion (AIC). We applied the method of seismic signal detection to continuous records collected over two years. The results show that the maximum value of network cross-correlation coefficients sampled from each constant interval can be approximated by the theory of extreme value statistics, which provides a parametric probability density function of maxima. By using the function, outliers can be considered with a reasonable criterion.