Machine Learning for Waveform Spectral Analysis on Nuclear Explosion Signal and Performance of Broadband Vertical Component

Abstract

Machine learning of nuclear explosion signal waveform is core component to realize the characteristics of signal. The processing of waveform explosion signal is broadly used for analysis of real time explosion signal. The numerous wavelet filters are developed by spectral synthesis using machine learning python to realize the signal characteristics. Our paper aims to generate the performance of nuclear explosion signal and processing the waveform from seismic sensor by using Continuous Wavelet Transform (CWT). CWT is also clearly to identify of spectral amplitudes and frequency-energy from component of signal seismic performed by Broadband Network in Indonesia. Finally, by machine learning python allows good time resolution for identified and performed of seismic signal from broadband which deployed in Indonesia.