Wavelet techniques for chaotic and fractal dynamics

dc.contributor.authorConstantine, William L. Ben_US
dc.date.accessioned2009-10-06T17:12:54Z
dc.date.available2009-10-06T17:12:54Z
dc.date.issued1999en_US
dc.descriptionThesis (Ph. D.)--University of Washington, 1999en_US
dc.description.abstractA novel wavelet based denoising technique is developed and shown to be more effective on average than waveshrink in denoising contaminated chaotic signals. A chaotic beam experiment is used to verify its effectiveness.Correlation dimension (D2) convergence issues for stochastic colored noise processes are revisited with the Gaussian Spectral Synthesis method. The inadequacies of the Phase Randomization method are discussed and is shown to be an inappropriate means to investigate D 2 convergence.A ensemble of nonlinear and linear measures is used to assess determinism and existing fractal structure in RR intervals from over 50 heart patients. Techniques are critiqued for their ability to classify disease states of the heart and predict the onset of fatal cardiac rhythms.en_US
dc.format.extentxvii, 315 p.en_US
dc.identifier.otherb43142126en_US
dc.identifier.other42655220en_US
dc.identifier.otherThesis 47970en_US
dc.identifier.urihttp://hdl.handle.net/1773/7124
dc.language.isoen_USen_US
dc.rightsCopyright is held by the individual authors.en_US
dc.rights.urien_US
dc.subject.otherTheses--Mechanical engineeringen_US
dc.titleWavelet techniques for chaotic and fractal dynamicsen_US
dc.typeThesisen_US

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