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Content Provider | IEEE Xplore Digital Library |
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Author | Yuchen Yao Swindlehurst, A.L. |
Copyright Year | 2011 |
Description | Author affiliation: Department of Electrical Engineering and Computer Science, University of California, Irvine, CA 92697, USA (Yuchen Yao; Swindlehurst, A.L.) |
Abstract | This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next. |
Starting Page | 4365 |
Ending Page | 4368 |
File Size | 544316 |
Page Count | 4 |
File Format | |
ISBN | 9781424441211 |
ISSN | 1557170X |
e-ISBN | 9781457715891 |
e-ISBN | 9781424441228 |
DOI | 10.1109/IEMBS.2011.6091083 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2011-08-30 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Vectors Heuristic algorithms Brain modeling Magnetic sensors Noise measurement Interference |
Content Type | Text |
Resource Type | Article |
Subject | Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition |
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