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Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

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Author

Summary, in English

In this paper, multiple windows, optimal for locally stationary processes (MW-LSP) are used to estimate the spectrogram of the electroencephalogram (EEG) where we focus on the ability to estimate transient frequency changes. A peak of known frequency was evoked in the EEG spectrum in a predetermined time interval, by using a 9 Hz flickering light. We investigate the multiple windows corresponding to the mean squared error optimal time-frequency kernel for estimation of the Wigner-Ville spectrum. The kernel is optimal for a certain locally stationary process where the covariance function is determined by two one-dimensional Gaussian functions

Department/s

Publishing year

2005

Language

English

Pages

7293-7296

Publication/Series

27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005

Volume

7 VOLS

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Probability Theory and Statistics

Keywords

  • Multiple windows
  • Covariance function
  • Locally stationary processes (MW-LSP)
  • Mean squared error optimal time-frequency kernel

Conference name

27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005.

Conference date

2005-09-01 - 2005-09-04

Conference place

Shanghai, China

Status

Published

Research group

  • Statistical Signal Processing Group

ISBN/ISSN/Other

  • ISSN: 0589-1019
  • ISBN: 0-7803-8741-4