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@PHDTHESIS{Beucker:39214,
author = {Beucker, R.},
title = {{P}arallele numerische {A}lgorithmen und mathematische
{T}heorie zur {M}agnetenzephalographie},
volume = {3630},
issn = {0944-2952},
school = {Techn. Hochsch. Aachen},
type = {Dr. (FH)},
address = {Jülich},
publisher = {Forschungszentrum, Zentralbibliothek},
reportid = {PreJuSER-39214, Juel-3630},
series = {Berichte des Forschungszentrums Jülich},
year = {1999},
note = {Record converted from VDB: 12.11.2012; Aachen, Techn.
Hochsch., Diss., 1999},
abstract = {Magnetoencephalography is a method for functional brain
imaging It is possible to estimate the location of sources
of biomagnetic activity in the brain using di erent
reconstruction methods Unfortunately the reconstruction
methods usually require a large amount of computation which
takes time It is important to get information about the
quality of the data directly after the measurement in order
to know if the data is worth processing further To get an
idea of the data quality in a timely manner a parallel
sliding window approach based on a multiple dipole
reconstruction method is developed for the massively
parallel computer system CRAY T E of the research centre
Julich Furthermore a special kind of minimumnorm method is
proposed which has some advantages with respect to stability
against noise The algorithm for the calculation of the
solution is implemented on the CRAY J of the research centre
Julich The problem of determing the number of active sources
for the sliding window approach is done with a statistical
test and the necessary improvement of the noise conditions
for the application of the test is solved by a multichannel
prewhitening method},
cin = {ZAM},
cid = {I:(DE-Juel1)VDB62},
pnm = {Mathematische Methoden und Algorithmen für neue
Rechnerstrukturen},
pid = {G:(DE-Juel1)FUEK105},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
url = {https://juser.fz-juelich.de/record/39214},
}