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Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

Sandsten, Maria LU and Sandberg, Johan LU (2005) 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. In 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005 7 VOLS. p.7293-7296
Abstract
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
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author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Multiple windows, Covariance function, Locally stationary processes (MW-LSP), Mean squared error optimal time-frequency kernel
in
27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005
volume
7 VOLS
pages
7293 - 7296
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
conference name
27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005.
external identifiers
  • wos:000238998406160
  • scopus:33846911322
ISSN
0589-1019
ISBN
0-7803-8741-4
DOI
10.1109/IEMBS.2005.1616195
language
English
LU publication?
yes
id
0585a16f-c154-49c8-a601-76759b45eb0f (old id 627390)
date added to LUP
2007-11-29 14:10:18
date last changed
2017-03-13 13:12:16
@inproceedings{0585a16f-c154-49c8-a601-76759b45eb0f,
  abstract     = {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},
  author       = {Sandsten, Maria and Sandberg, Johan},
  booktitle    = {27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005},
  isbn         = {0-7803-8741-4},
  issn         = {0589-1019},
  keyword      = {Multiple windows,Covariance function,Locally stationary processes (MW-LSP),Mean squared error optimal time-frequency kernel},
  language     = {eng},
  pages        = {7293--7296},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  title        = {Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram},
  url          = {http://dx.doi.org/10.1109/IEMBS.2005.1616195},
  volume       = {7 VOLS},
  year         = {2005},
}