Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/6179
AuthorsAdelfio, Giada 
Chiodi, Marcello 
D'Alessandro, Antonino 
Luzio, Dario 
TitleClustering of Waveforms Based on FPCA Direction
Issue Date21-Jul-2010
URIhttp://hdl.handle.net/2122/6179
KeywordsFPCA
Waveforms clustering
Subject Classification04. Solid Earth::04.06. Seismology::04.06.99. General or miscellaneous 
AbstractAbstract. Looking for curves similarity could be a complex issue characterized by subjective choices related to continuous transformations of observed discrete data (Chiodi, 1989). Waveforms correlation techniques have been introduced to charac- terize the degree of seismic event similarity (Menke, 1999) and in facilitating more accurate relative locations within similar event clusters by providing more precise timing of seismic wave (P and S) arrivals (Phillips, 1997). In this paper functional analysis (Ramsey, and Silverman, 2006) is considered to highlight common characteristics of waveforms-data and to summarize these charac- teristics by few components, by applying a variant of a classical clustering method to rotated data (Sangalli et al., 2010) according to the direction of maximum variance (i.e. based on PCA rotation of data).
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