Wavelet Smoothing of Evolutionary Spectra by Non-Linear Thresholding

  • We consider wavelet estimation of the time-dependent (evolutionary) power spectrum of a locally stationary time series. Allowing for departures from stationary proves useful for modelling, e.g., transient phenomena, quasi-oscillating behaviour or spectrum modulation. In our work wavelets are used to provide an adaptive local smoothing of a short-time periodogram in the time-freqeuncy plane. For this, in contrast to classical nonparametric (linear) approaches we use nonlinear thresholding of the empirical wavelet coefficients of the evolutionary spectrum. We show how these techniques allow for both adaptively reconstructing the local structure in the time-frequency plane and for denoising the resulting estimates. To this end a threshold choice is derived which is motivated by minimax properties w.r.t. the integrated mean squared error. Our approach is based on a 2-d orthogonal wavelet transform modified by using a cardinal Lagrange interpolation function on the finest scale. As an example, we apply our procedure to a time-varying spectrum motivated from mobile radio propagation.

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Metadaten
Author:Rainer von Sachs, Kai Schneider
URN (permanent link):urn:nbn:de:hbz:386-kluedo-5030
Serie (Series number):Berichte der Arbeitsgruppe Technomathematik (AGTM Report) (106)
Document Type:Article
Language of publication:English
Year of Completion:1999
Year of Publication:1999
Publishing Institute:Technische Universität Kaiserslautern
Tag:evolutionary spectrum ; locally stationary process ; minimax rate; nonlinear wavelet thresholding ; short-time periodogram
Source:Applied and Computional Harmonic Analysis 3, 268-282 (1996)
Faculties / Organisational entities:Fachbereich Mathematik
DDC-Cassification:510 Mathematik

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