The discrimination of natural earthquakes and quarry blasts is an important part of
earthquake monitoring and early warning. In recent years, the fast-developing deep learning …

摘要天然地震和爆破事件识别是地震监测预警的重要内容. 近年来, 快速发展的深度学习算法以
其强大的数据特征挖掘和图像识别能力, 能够较快并准确地约束地震事件属性 …

In the seismic event classification, determining the seismic features of rockfall is significantly
important for the automatic classification of seismic events because of the huge amount of …

This work deals with the analysis of daily and minute sampled financial stock market data.
We propose a Dynamic Fourier Transform (DFT) and a Wavelet Transform to estimate the …

In this study, we apply a wavelet methodology initially developed for geophysical data to
financial data. Specifically, the method distinguishes between natural tectonic earthquakes …

A sequence of intraplate earthquakes occurred in Arizona at the same location where
mining explosions were carried out in previous years. The explosions and some of the …

In this study, we have analyzed the long memory effects of earthquake time series and
volcano volcanic eruptions. By using a class of auto-regressive techniques, we studied the …

利用天然地震震源和人工爆破震源之间信号能量分布的差异, 结合RBF 神经网络技术, 对2
类事件进行分类, 具体步骤如下: 使用8 个带通滤波器对事件波形进行滤波, 并划分为4 个波形段 …

In this work, we explore the use of Lévy flight and wavelet techniques as a tool for
investigating the statistical properties of the seismic signals generated during volcanic …

Presents a multitude of topics relevant to the quantitative finance community by combining
the best of the theory with the usefulness of applications Written by accomplished teachers …