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dc.contributor.authorČastová, Nina
dc.contributor.authorHorák, David
dc.contributor.authorKaláb, Zdeněk
dc.date.accessioned2006-11-15T06:11:49Z
dc.date.available2006-11-15T06:11:49Z
dc.date.issued2006
dc.identifier.citationInternational Journal of Wavelets, Multiresolution and Information Processing. 2006, vol. 4, no. 3, p. 405-414.en
dc.identifier.issn0219-6913
dc.identifier.urihttp://hdl.handle.net/10084/58147
dc.language.isoenen
dc.publisherWorld Scientific Publishingen
dc.relation.ispartofseriesInternational Journal of Wavelets, Multiresolution and Information Processingen
dc.relation.urihttps://doi.org/10.1142/S0219691306001336en
dc.subjectwavelet transformen
dc.subjecttime frequency spectraen
dc.subjectseismological dataen
dc.titleDescription of seismic events using wavelet transformen
dc.typearticleen
dc.identifier.locationNení ve fondu ÚKen
dc.description.abstract-enThis paper deals with engineering application of wavelet transform for processing of real seismological signals. Methodology for processing of these slight signals using wavelet transform is presented in this paper. Briefly, three basic aims are connected with this procedure: 1. Selection of optimal wavelet and optimal wavelet basis B-opt for selected data set based on minimal entropy: B-opt = axg min(B) E(X, B). The best results were reached by symmetric complex wavelets with scaling coefficients SCD-6. 2. Wavelet packet decomposition and filtration of data using universal criterion of thresholding of the form lambda = sigma root 2 ln(n), where sigma is minimal variance of the sum of packet decomposition of chosen level. 3. Cluster analysis of decomposed data. All programs were elaborated using program MATLAB 5.en
dc.identifier.doi10.1142/S0219691306001336
dc.identifier.wos000241441700002


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