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dc.degree.departmentStatisticsen_US
dc.rights.availabilityUnrestricted.
dc.creatorKwan, Johnny Chun Man
dc.date.accessioned2016-11-14T23:09:50Z
dc.date.available2011-02-18T19:01:22Z
dc.date.available2016-11-14T23:09:50Z
dc.date.issued1999-05
dc.identifier.urihttp://hdl.handle.net/2346/9090en_US
dc.description.abstractIn this thesis, the issue of estimating intermittency rates in localized phenomena using wavelets will be addressed. This problem was earlier addressed by Gamage and Hagelberg in [6,8,9]. Here we present an approached based on coherent structure detection. The statistical problem is different from detecting single events, in which the false alarm rate (concluding the signal is coherent when it is actually not) or the size of the test must be controlled for the entire time series. Our new statistical technique controls the false alarm rate for each scale at each time sample, thereby controlling the total false alarm intermittency rate. This is done with a scale-dependent threshold for the wavelet coefficients, which allows two conclusions: that a signal contains intermittent localized phenomena, and that these phenomena are localized to specific time intervals in the signal. The algorithm is statistically rigorous and appropriate for long time series.
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherTexas Tech Universityen_US
dc.subjectWavelets (Mathematics)en_US
dc.subjectSignal processingen_US
dc.subjectTurbulenceen_US
dc.titleWavelets and turbulence
dc.typeThesis


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