Infrasonic data at volcanoes have been increasingly analyzed to get information about eruptive activity. Wind noise is an important problem, which cannot be solved using more classical seismological techniques such as deconvolution (Robinson, 1967), as the interaction between wind and original signal cannot be modeled simply as a convolution. The problem has therefore been tackled with a wide spectrum of original approaches, from the use of sensor arrays (Ripepe and Marchetti, 2002; Matoza et al., 2011), to spatial filters consisting of a network of pipes (Hedlin et al., 2003) or the...
Filtering Wind in Infrasound Data by Non‐Negative Matrix Factorization
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Roberto Carniel, Giuseppe Cabras, Mie Ichihara, Minoru Takeo; Filtering Wind in Infrasound Data by Non‐Negative Matrix Factorization. Seismological Research Letters 2014;; 85 (5): 1056–1062. doi: https://doi.org/10.1785/0220130142
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