Information criteria determine the number of active sources

T.R. Knosche; E.M. Berends; M.J. Peters; H.R.A. Jagers

doi:10.1109/IEMBS.1996.651992

Information criteria determine the number of active sources

T.R. Knosche
, E.M. Berends
, M.J. Peters
, H.R.A. Jagers

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

154 Downloads (Pure)

Abstract

With the neuroelectromagnetic inverse problem, the optimal choice of the number of sources is a difficult problem, especially in the presence of correlated noise. In this paper we present a number of information criteria that help to solve this problem. They are based on the probability density function of the measurements or their eigenvalues. Make use of the Akaike or MDL (minimum description length) correction term and all employ some sort of noise information. By extensive simulations we investigated the conditions under which these criteria yield reliable estimations. We were able to quantify two major factors of influence: (1) the precision of the noise information and (2) the signal-to-noise ratio (SNR). Here defined as the ratio of the smallest signal eigenvalues and the average of the noise eigenvalues. Furthermore, we found that the Akaike correction term tends to overestimate, due to its greater sensibility to the precision of the noise information

Original language	English
Title of host publication	Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Place of Publication	Los Alamitos, CA
Publisher	IEEE
Pages	83-87
Number of pages	5
Volume	2
ISBN (Print)	0-7803-3811-1
DOIs	https://doi.org/10.1109/IEMBS.1996.651992
Publication status	Published - 30 Sept 1996
Event	18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996: Bridging Disciplines for Biomedicine - Amsterdam, Netherlands Duration: 31 Oct 1996 → 3 Nov 1996 Conference number: 18

Conference

Conference	18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996
Abbreviated title	EMBC
Country/Territory	Netherlands
City	Amsterdam
Period	31/10/96 → 3/11/96

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10.1109/IEMBS.1996.651992

Knosche1996informationFinal published version, 326 KB

1 Conference contribution

Information criteria determine the number of active sources
Knosche, T. R., Berends, E. M., Peters, M. J. & Jagers, H. R. A., 14 Dec 1997, Quantitative and topologival EEG and MEG analysis: Proceedings of the 3rd Hans Berger Congress. Witte, H. (ed.). Jena, Germany: Karl Mayer GmbH, p. 321-323 3 p.
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Cite this

@inproceedings{99fa35367d48415d80ecc9bfc440734d,

title = "Information criteria determine the number of active sources",

abstract = "With the neuroelectromagnetic inverse problem, the optimal choice of the number of sources is a difficult problem, especially in the presence of correlated noise. In this paper we present a number of information criteria that help to solve this problem. They are based on the probability density function of the measurements or their eigenvalues. Make use of the Akaike or MDL (minimum description length) correction term and all employ some sort of noise information. By extensive simulations we investigated the conditions under which these criteria yield reliable estimations. We were able to quantify two major factors of influence: (1) the precision of the noise information and (2) the signal-to-noise ratio (SNR). Here defined as the ratio of the smallest signal eigenvalues and the average of the noise eigenvalues. Furthermore, we found that the Akaike correction term tends to overestimate, due to its greater sensibility to the precision of the noise information",

author = "T.R. Knosche and E.M. Berends and M.J. Peters and H.R.A. Jagers",

year = "1996",

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doi = "10.1109/IEMBS.1996.651992",

language = "English",

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volume = "2",

pages = "83--87",

booktitle = "Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society",

publisher = "IEEE",

address = "United States",

note = "18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996 : Bridging Disciplines for Biomedicine, EMBC ; Conference date: 31-10-1996 Through 03-11-1996",

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Knosche, TR, Berends, EM, Peters, MJ & Jagers, HRA 1996, Information criteria determine the number of active sources. in Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. vol. 2, IEEE, Los Alamitos, CA, pp. 83-87, 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996, Amsterdam, Netherlands, 31/10/96. https://doi.org/10.1109/IEMBS.1996.651992

Information criteria determine the number of active sources. / Knosche, T.R.; Berends, E.M.; Peters, M.J. et al.
Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol. 2 Los Alamitos, CA: IEEE, 1996. p. 83-87.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Information criteria determine the number of active sources

AU - Knosche, T.R.

AU - Berends, E.M.

AU - Peters, M.J.

AU - Jagers, H.R.A.

N1 - Conference code: 18

PY - 1996/9/30

Y1 - 1996/9/30

N2 - With the neuroelectromagnetic inverse problem, the optimal choice of the number of sources is a difficult problem, especially in the presence of correlated noise. In this paper we present a number of information criteria that help to solve this problem. They are based on the probability density function of the measurements or their eigenvalues. Make use of the Akaike or MDL (minimum description length) correction term and all employ some sort of noise information. By extensive simulations we investigated the conditions under which these criteria yield reliable estimations. We were able to quantify two major factors of influence: (1) the precision of the noise information and (2) the signal-to-noise ratio (SNR). Here defined as the ratio of the smallest signal eigenvalues and the average of the noise eigenvalues. Furthermore, we found that the Akaike correction term tends to overestimate, due to its greater sensibility to the precision of the noise information

AB - With the neuroelectromagnetic inverse problem, the optimal choice of the number of sources is a difficult problem, especially in the presence of correlated noise. In this paper we present a number of information criteria that help to solve this problem. They are based on the probability density function of the measurements or their eigenvalues. Make use of the Akaike or MDL (minimum description length) correction term and all employ some sort of noise information. By extensive simulations we investigated the conditions under which these criteria yield reliable estimations. We were able to quantify two major factors of influence: (1) the precision of the noise information and (2) the signal-to-noise ratio (SNR). Here defined as the ratio of the smallest signal eigenvalues and the average of the noise eigenvalues. Furthermore, we found that the Akaike correction term tends to overestimate, due to its greater sensibility to the precision of the noise information

U2 - 10.1109/IEMBS.1996.651992

DO - 10.1109/IEMBS.1996.651992

M3 - Conference contribution

SN - 0-7803-3811-1

VL - 2

SP - 83

EP - 87

BT - Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

PB - IEEE

CY - Los Alamitos, CA

T2 - 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 1996

Y2 - 31 October 1996 through 3 November 1996

ER -

Information criteria determine the number of active sources

Abstract

Conference

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Information criteria determine the number of active sources

Cite this