Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

Maria Sandsten; Johan Sandberg

doi:10.1109/IEMBS.2005.1616195

Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

Maria Sandsten, Johan Sandberg

Mathematical Statistics

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

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

Original language	English
Title of host publication	27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
Pages	7293-7296
Volume	7 VOLS
ISBN (Print)	0-7803-8741-4
DOIs	https://doi.org/10.1109/IEMBS.2005.1616195
Publication status	Published - 2005
Event	27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. - Shanghai, China Duration: 2005 Sept 1 → 2005 Sept 4 Conference number: 27

Publication series

Name
Volume	7 VOLS
ISSN (Print)	0589-1019

Conference

Conference	27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005.
Abbreviated title	IEEE-EMBS 2005
Country/Territory	China
City	Shanghai
Period	2005/09/01 → 2005/09/04

Subject classification (UKÄ)

Probability Theory and Statistics

Free keywords

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

Access to Document

10.1109/IEMBS.2005.1616195

Cite this

Sandsten, M., & Sandberg, J. (2005). Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram. In 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005 (Vol. 7 VOLS, pp. 7293-7296). IEEE - Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IEMBS.2005.1616195

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title = "Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram",

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",

keywords = "Multiple windows, Covariance function, Locally stationary processes (MW-LSP), Mean squared error optimal time-frequency kernel",

author = "Maria Sandsten and Johan Sandberg",

year = "2005",

doi = "10.1109/IEMBS.2005.1616195",

language = "English",

isbn = "0-7803-8741-4",

volume = "7 VOLS",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

pages = "7293--7296",

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

address = "United States",

note = "27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. , IEEE-EMBS 2005 ; Conference date: 01-09-2005 Through 04-09-2005",

}

Sandsten, M & Sandberg, J 2005, Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram. in 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. vol. 7 VOLS, IEEE - Institute of Electrical and Electronics Engineers Inc., pp. 7293-7296, 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. , Shanghai, China, 2005/09/01. https://doi.org/10.1109/IEMBS.2005.1616195

Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram. / Sandsten, Maria; Sandberg, Johan.
27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. Vol. 7 VOLS IEEE - Institute of Electrical and Electronics Engineers Inc., 2005. p. 7293-7296.

Research output: Chapter in Book/Report/Conference proceeding › Paper in conference proceeding › peer-review

TY - GEN

T1 - Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

AU - Sandsten, Maria

AU - Sandberg, Johan

N1 - Conference code: 27

PY - 2005

Y1 - 2005

N2 - 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

AB - 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

KW - Multiple windows

KW - Covariance function

KW - Locally stationary processes (MW-LSP)

KW - Mean squared error optimal time-frequency kernel

UR - https://www.scopus.com/pages/publications/33846911322

U2 - 10.1109/IEMBS.2005.1616195

DO - 10.1109/IEMBS.2005.1616195

M3 - Paper in conference proceeding

C2 - 17281964

SN - 0-7803-8741-4

VL - 7 VOLS

SP - 7293

EP - 7296

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

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 27th Annual International Conference of the Engineering in Medicine and Biology Society, 2005.

Y2 - 1 September 2005 through 4 September 2005

ER -

Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

Abstract

Publication series

Conference

Subject classification (UKÄ)

Free keywords

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Statistical Signal Processing Group

Cite this

Multiple Windows for Estimation of Locally Stationary Transients in the Electroencephalogram

Abstract

Publication series

Conference

Subject classification (UKÄ)

Free keywords

Access to Document

Other files and links

Fingerprint

Projects

Statistical Signal Processing Group

Cite this