Title
Evaluating robustness of a HMM-based classification system of volcano-seismic events at colima and popocatepetl volcanoes
Abstract
This work presents a continuous volcano-seismic classification system based in the Hidden Markov Models as solution to recently strong needs for automatic event detection and recognition methods in early warning and monitoring scenarios. Furthermore, our system includes a reliable method to assign confidence measures to the recognized signals in order to evaluate the robustness of the results. Data from the two most active volcanoes have been used to probe the system reliability on a complex joint corpus achieving a recognition accuracy higher than 78% in blind recognition tests.
Year
DOI
Venue
2009
10.1109/IGARSS.2009.5418275
Geoscience and Remote Sensing Symposium,2009 IEEE International,IGARSS 2009
Keywords
Field
DocType
geophysical signal processing,hidden Markov models,robust control,seismology,volcanology,Colima volcano,HMM-based classification system,Hidden Markov Models,Mexico,Popocatepetl volcano,automatic event detection,blind recognition tests,recognition methods,robustness evaluation,volcano monitoring,volcano-seismic events,Hidden Markov Models,classification,reliability,volcano monitoring,volcano-seismic events
Warning system,Mel-frequency cepstrum,Volcano,System testing,Spectrogram,Computer science,Remote sensing,Robustness (computer science),Hidden Markov model,Robust control
Conference
Volume
ISSN
ISBN
2
2153-6996
978-1-4244-3395-7
Citations 
PageRank 
References 
2
0.36
0
Authors
8