Waveform analysis of broadband seismic station using machine learning Python based on Morlet wavelet

Wavelet signal processing is broadly used for analysis of real time seismic signal. The numerous wavelet filters are developed by spectral synthesis using machine learning python to realize the signal characteristics. Our paper aims to solve and evaluating the frequencies-energy characteristic of ea...

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Bibliographic Details
Published in:IOP conference series. Materials Science and Engineering 2018-10, Vol.420 (1), p.12048
Main Authors: Darnila, Eva, Ula, Mutammimul, Tarigan, Kerista, Limbong, Tonni, Sinambela, Marzuki
Format: Article
Language:English
Subjects:
Broadband
Continuous wavelet transform
Electromagnetic wave filters
Machine learning
Morlet wavelet
Seismograms
Signal processing
Waveforms
Wavelet analysis
Wavelet transforms
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Summary:Wavelet signal processing is broadly used for analysis of real time seismic signal. The numerous wavelet filters are developed by spectral synthesis using machine learning python to realize the signal characteristics. Our paper aims to solve and evaluating the frequencies-energy characteristic of earthquake. The wavelet method by Continuous Wavelet Transform (CWT) is able to clearly and simultaneously of amplitudes and frequency-energy from component between the seismogram which seismic sensor broadband recorded in the January 16, 2017 in Medan, North Sumatra. Finally, from machine learning python with morlet wavelet allows good time resolution for high frequencies, and good frequency resolution for low frequencies.
ISSN:1757-8981
1757-899X
1757-899X
DOI:10.1088/1757-899X/420/1/012048