Reducing wind noise in seismic data using non-negative matrix factorization: An application to Villarrica volcano, Chile

Cabras, Giuseppe; CARNIEL, Roberto; Jones, Joshua P.; Takeo, Minoru

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Single channel source separation of seismic signals is an appealing but difficult problem. In this paper, we introduce a semi-blind single-channel seismic source separation method to enhance the components of volcanic origin. In this method, the source decomposition scheme is addressed as a Sparse Non-negative Matrix Factorization (NMF) of the time-frequency representation of the single vertical seismic channel. As a case study we present an application using seismic data recorded at Villarrica volcano, Chile, one of the most active in the southern Andes. The analysed dataset is strongly contaminated by wind noise and the procedure is used to separate a component of volcanic origin from another of meteorological origin.

Titolo:	Reducing wind noise in seismic data using non-negative matrix factorization: An application to Villarrica volcano, Chile
Autori:	Cabras, Giuseppe CARNIEL, Roberto Jones, Joshua P. Takeo, Minoru mostra contributor esterni nascondi contributor esterni
Data di pubblicazione:	2014
Rivista:	GEOFÍSICA INTERNACIONAL
Citazione:	Reducing wind noise in seismic data using non-negative matrix factorization: An application to Villarrica volcano, Chile / Cabras, Giuseppe; Carniel, Roberto; Jones, Joshua P.; Takeo, Minoru. - In: GEOFÍSICA INTERNACIONAL. - ISSN 0016-7169. - 53:1(2014), pp. 77-85.
Abstract:	Single channel source separation of seismic signals is an appealing but difficult problem. In this paper, we introduce a semi-blind single-channel seismic source separation method to enhance the components of volcanic origin. In this method, the source decomposition scheme is addressed as a Sparse Non-negative Matrix Factorization (NMF) of the time-frequency representation of the single vertical seismic channel. As a case study we present an application using seismic data recorded at Villarrica volcano, Chile, one of the most active in the southern Andes. The analysed dataset is strongly contaminated by wind noise and the procedure is used to separate a component of volcanic origin from another of meteorological origin.
Handle:	http://hdl.handle.net/11390/1084461
Appare nelle tipologie:	1.1 Articolo in rivista

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