Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/739
AuthorsChianese, D.* 
Colangelo, G.* 
D'Emilio, M.* 
Lanfredi, M.* 
Lapenna, V.* 
Ragosta, M.* 
Macchiato, M. F.* 
TitleWavelet analysis as a tool to characteriseand remove environmental noisefrom self-potential time series
Issue Date2004
Series/Report no.47 (1)
URIhttp://hdl.handle.net/2122/739
Keywordsself-potential signals
wavelet analysis
Subject Classification04. Solid Earth::04.02. Exploration geophysics::04.02.07. Instruments and techniques 
AbstractMultiresolution wavelet analysis of self-potential signals and rainfall levels is performed for extracting fluctuations in electrical signals, which might be addressed to meteorological variability. In the time-scale domain of the wavelet transform, rain data are used as markers to single out those wavelet coefficients of the electric signal which can be considered relevant to the environmental disturbance. Then these coefficients are filtered out and the signal is recovered by anti-transforming the retained coefficients. Such methodological approach might be applied to characterise unwanted environmental noise. It also can be considered as a practical technique to remove noise that can hamper the correct assessment and use of electrical techniques for the monitoring of geophysical phenomena.
Appears in Collections:Annals of Geophysics

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