Hybrid Linear/Quadratic Time-Frequency Attributes

dc.citation.bibtexNamearticleen_US
dc.citation.firstpage760
dc.citation.issueNumber4en_US
dc.citation.journalTitleIEEE Transactions on Signal Processingen_US
dc.citation.lastpage766
dc.citation.volumeNumber49en_US
dc.contributor.authorBaraniuk, Richard G.en_US
dc.contributor.authorCoates, Mark J.en_US
dc.contributor.authorSteeghs, Philippeen_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:36:19Z
dc.date.available2007-10-31T00:36:19Z
dc.date.issued2001-04-01en
dc.date.modified2006-07-19en_US
dc.date.submitted2006-06-06en_US
dc.descriptionJournal Paperen_US
dc.description.abstractWe present an efficient method for robustly calculating time-frequency attributes of a signal, including instantaneous mean frequency, bandwidth, kurtosis, and other moments. Most current attribute estimation techniques involve a costly intermediate step of computing a (highly oversampled) two-dimensonal (2-D) quadratic time-frequency representation (TFR), which is then collapsed to the one-dimensonal (1-D) attribute. Using the principles of hybrid linear/quadratic time-frequency analysis (time-frequency distribution series), we propose computing attributes as nonlinear combinations of the (slightly oversampled) linear Gabor coefficients of the signal. The method is both computationally efficient and accurate; it performs as well as the best techniques based on adaptive TFRs. To illustrate, we calculate an attribute of a seismic cross section.en_US
dc.identifier.citationR. G. Baraniuk, M. J. Coates and P. Steeghs, "Hybrid Linear/Quadratic Time-Frequency Attributes," <i>IEEE Transactions on Signal Processing,</i> vol. 49, no. 4, 2001.
dc.identifier.doihttp://dx.doi.org/10.1109/78.912920en_US
dc.identifier.urihttps://hdl.handle.net/1911/19715
dc.language.isoeng
dc.subjectGabor coefficients*
dc.subject.keywordGabor coefficientsen_US
dc.subject.otherDSP for Communicationsen_US
dc.titleHybrid Linear/Quadratic Time-Frequency Attributesen_US
dc.typeJournal article
dc.type.dcmiText
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