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Optimal Multitaper Wigner Spectrum Estimation of a Class of Locally Stationary Processes Using Hermite Functions

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Author

Summary, in English

This paper investigates the time-discrete multitapers that give a mean square error optimal Wigner spectrum estimate for a class of locally stationary processes (LSPs). The accuracy in the estimation of the time-variable Wigner spectrum of the LSP is evaluated and compared with other frequently used methods. The optimal multitapers are also approximated by Hermite functions, which is computationally more efficient, and the errors introduced by this approximation are studied. Additionally, the number of windows included in a multitaper spectrum estimate is often crucial and an investigation of the error caused by limiting this number is made. Finally, the same optimal set of weights can be stored and utilized for different window lengths. As a result, the optimal multitapers are shown to be well approximated by Hermite functions, and a limited number of windows can be used for a mean square error optimal spectrogram estimate.

Department/s

Publishing year

2011

Language

English

Publication/Series

Eurasip Journal on Advances in Signal Processing

Document type

Journal article

Publisher

Hindawi Limited

Topic

  • Probability Theory and Statistics

Status

Published

Research group

  • Statistical Signal Processing
  • Stochastics in Medicine
  • Statistical Signal Processing Group

ISBN/ISSN/Other

  • ISSN: 1687-6172