Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model

L. J. Waldorp; H. M. Huizenga; C. V. Dolan; P. C.M. Molenaar

doi:10.1109/10.923793

Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model

L. J. Waldorp
, H. M. Huizenga
, C. V. Dolan
, P. C.M. Molenaar

Human Development and Family Studies

Research output: Contribution to journal › Article › peer-review

26 Scopus citations

Abstract

Estimated generalized least squares (EGLS) electromagnetic source analysis is used to downweight noisy and correlated data. Standard EGLS requires many trials to accurately estimate the noise covariances and, thus, the source parameters. Alternatively, the noise covariances can be modeled parametrically. Only the parameters of the model describing the noise covariances need to be estimated and, therefore, less trials are required. This method is referred to as parametric egls (PEGLS). In this paper, PEGLS is developed and its performance is tested in a simulation study and in a pseudoempirical study.

Original language	English (US)
Pages (from-to)	737-741
Number of pages	5
Journal	IEEE Transactions on Biomedical Engineering
Volume	48
Issue number	6
DOIs	https://doi.org/10.1109/10.923793
State	Published - 2001

All Science Journal Classification (ASJC) codes

Biomedical Engineering

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10.1109/10.923793

Cite this

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title = "Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model",

abstract = "Estimated generalized least squares (EGLS) electromagnetic source analysis is used to downweight noisy and correlated data. Standard EGLS requires many trials to accurately estimate the noise covariances and, thus, the source parameters. Alternatively, the noise covariances can be modeled parametrically. Only the parameters of the model describing the noise covariances need to be estimated and, therefore, less trials are required. This method is referred to as parametric egls (PEGLS). In this paper, PEGLS is developed and its performance is tested in a simulation study and in a pseudoempirical study.",

author = "Waldorp, \{L. J.\} and Huizenga, \{H. M.\} and Dolan, \{C. V.\} and Molenaar, \{P. C.M.\}",

note = "Funding Information: Manuscript received June 7, 2000; revised February 23, 2001. This work was supported by The Netherlands Organization for Scientific Research (NWO). The work of L. J. Waldorp was supported by the NWO Foundation for Behavioral and Educational Sciences of this organization under Grant 527-25-013 awarded to H. M. Huizenga. The work of H. Huizenga and C. V. Dolan was supported by fellowships from the Royal Netherlands Acadamy of Arts and Sciences. Asterisk indicates corresponding author. *L. J. Waldrop is with the Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018 WB Amsterdam, The Netherlands (e-mail: [email protected]).",

year = "2001",

doi = "10.1109/10.923793",

language = "English (US)",

volume = "48",

pages = "737--741",

journal = "IEEE Transactions on Biomedical Engineering",

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TY - JOUR

T1 - Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model

AU - Waldorp, L. J.

AU - Huizenga, H. M.

AU - Dolan, C. V.

AU - Molenaar, P. C.M.

N1 - Funding Information: Manuscript received June 7, 2000; revised February 23, 2001. This work was supported by The Netherlands Organization for Scientific Research (NWO). The work of L. J. Waldorp was supported by the NWO Foundation for Behavioral and Educational Sciences of this organization under Grant 527-25-013 awarded to H. M. Huizenga. The work of H. Huizenga and C. V. Dolan was supported by fellowships from the Royal Netherlands Acadamy of Arts and Sciences. Asterisk indicates corresponding author. *L. J. Waldrop is with the Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018 WB Amsterdam, The Netherlands (e-mail: [email protected]).

PY - 2001

Y1 - 2001

N2 - Estimated generalized least squares (EGLS) electromagnetic source analysis is used to downweight noisy and correlated data. Standard EGLS requires many trials to accurately estimate the noise covariances and, thus, the source parameters. Alternatively, the noise covariances can be modeled parametrically. Only the parameters of the model describing the noise covariances need to be estimated and, therefore, less trials are required. This method is referred to as parametric egls (PEGLS). In this paper, PEGLS is developed and its performance is tested in a simulation study and in a pseudoempirical study.

AB - Estimated generalized least squares (EGLS) electromagnetic source analysis is used to downweight noisy and correlated data. Standard EGLS requires many trials to accurately estimate the noise covariances and, thus, the source parameters. Alternatively, the noise covariances can be modeled parametrically. Only the parameters of the model describing the noise covariances need to be estimated and, therefore, less trials are required. This method is referred to as parametric egls (PEGLS). In this paper, PEGLS is developed and its performance is tested in a simulation study and in a pseudoempirical study.

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JO - IEEE Transactions on Biomedical Engineering

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ER -

Estimated generalized least squares electromagnetic source analysis based on a parametric noise covariance model

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