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dc.contributor.authorÖzdemir, A. Kemalen_US
dc.contributor.authorArıkan, Orhanen_US
dc.coverage.spatialIstanbul, Turkey
dc.date.accessioned2016-02-08T11:58:44Z
dc.date.available2016-02-08T11:58:44Z
dc.date.issued2000-06en_US
dc.identifier.issn0736-7791
dc.identifier.urihttp://hdl.handle.net/11693/27650
dc.descriptionDate of Conference: 5-9 June 2000
dc.description.abstractA novel algorithm is proposed for efficiently smoothing the slices of the Wigner distribution by exploiting the recently developed relation between the Radon transform of the ambiguity function and the fractional Fourier transformation. The main advantage of the new algorithm is its ability to suppress cross-term interference on chirp-like auto-components without any detrimental effect to the auto-components. For a signal with N samples, the computational complexity of the algorithm is O(N log N) flops for each smoothed slice of the Wigner distribution.en_US
dc.language.isoEnglishen_US
dc.source.title2000 IEEE International Conference on Acoustics, Speech and Signal Processing. Proceedingsen_US
dc.relation.isversionofhttps://doi.org/10.1109/ICASSP.2000.859054
dc.subjectAlgorithmsen_US
dc.subjectComputational complexityen_US
dc.subjectComputer simulationen_US
dc.subjectFast Fourier transformsen_US
dc.subjectInterference suppressionen_US
dc.subjectLow pass filtersen_US
dc.subjectProbability distributionsen_US
dc.subjectFractional Fourier transformen_US
dc.subjectRadon transformen_US
dc.subjectSuppress cross term interferenceen_US
dc.subjectTime frequency representationen_US
dc.subjectWigner distributionen_US
dc.subjectAdaptive filteringen_US
dc.titleHigh resolution time frequency representation with significantly reduced cross-termsen_US
dc.typeConference Paperen_US
dc.departmentDepartment of Electrical and Electronics Engineeringen_US
dc.citation.spage693en_US
dc.citation.epage696en_US
dc.identifier.doi10.1109/ICASSP.2000.859054
dc.publisherIEEEen_US
dc.contributor.bilkentauthorArıkan, Orhan
buir.contributor.orcidArıkan, Orhan|0000-0002-3698-8888en_US


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