Realization and comparison of P- and S- seismic phases detection algorithms using neural networks
Abstract
The diploma thesis studies the implementation and comparison of algorithms for P- and S- seismic phases detection, using neural networks. The thesis is structured in 6 chapters: Chapter 1 presents the principles of seismology, earthquake generation, seismic waves and their recording and seismic phases P and S. Chapter 2 summarizes the state-of-the-art in seismic phases detection using polarization, energy and autoregressive models. Neural networks are detailed in Chapter 3, in terms of principles, architectures, use and advantages. Chapters 4 and 5 present a framework that utilizes neural networks for seismic phase detection (P and S accordingly). The last chapter 6 presents the conclusions of the thesis and indicate future research work. In the appendices, all experimental results are presented in tables along with various statistics.
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Published as:
I. N. Athanasiadis,
Realization and comparison of P- and S- seismic phases detection algorithms using neural networks,
MSc Thesis, pg. 98,
2000, Aristotle University of Thessaloniki.
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