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Kernels and multiple windows for estimation of the Wigner-Ville spectrum of Gaussian locally stationary processes
Univ. of Newcastle.
Lund University.
2007 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 55, no 1, 73-84 p.Article in journal (Refereed) Published
Abstract [en]

This paper treats estimation of the Wigner-Ville spectrum (WVS) of Gaussian continuous-time stochastic processes using Cohen's class of time-frequency representations of random signals. We study the minimum mean square error estimation kernel for locally stationary processes in Silverman's sense, and two modifications where we first allow chirp multiplication and then allow nonnegative linear combinations of covariances of the first kind. We also treat the equivalent multitaper estimation formulation and the associated problem of eigenvalue-eigenfunction decomposition of a certain Hermitian function. For a certain family of locally stationary processes which parametrizes the transition from stationarity to nonstationarity, the optimal windows are approximately dilated Hermite functions. We determine the optimal coefficients and the dilation factor for these functions as a function of the process family parameter.

Place, publisher, year, edition, pages
Piscataway: IEEE Press, 2007. Vol. 55, no 1, 73-84 p.
Keyword [en]
Locally stationary circular symmetric processes, multitaper spectral estimation, optimal estimation, time-frequency analysis, Wigner-Ville spectrum (WVS).
National Category
Signal Processing
Research subject
Physics, Waves and Signals
Identifiers
URN: urn:nbn:se:lnu:diva-27586DOI: 10.1109/TSP.2006.882076OAI: oai:DiVA.org:lnu-27586DiVA: diva2:637388
Available from: 2013-07-17 Created: 2013-07-17 Last updated: 2017-12-06Bibliographically approved

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Wahlberg, Patrik

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  • de-DE
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  • nn-NB
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  • Other locale
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  • asciidoc
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