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Andreas Galka

Showing results (1-10 of 30) with videos related to

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Entropy (Basel, Switzerland)|July 29, 2023
Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A ReviewFumikazu Miwakeichi, Andreas Galka
Entropy (Basel, Switzerland)|October 28, 2023
State Space Modeling of Event Count Time SeriesSidratul Moontaha, Bert Arnrich, Andreas Galka
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
Analysis of the effects of medication for the treatment of epilepsy by ensemble Iterative Extended Kalman filteringSidratul Moontaha, Andreas Galka, Thomas Meurer, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
Muscle artifact suppression using independent-component analysis and state-space modelingAlina Santillán-Guzmán, Ulrich Heute, Ulrich Stephani, et al.
Cognitive Neurodynamics|November 13, 2008
A data-driven model of the generation of human EEG based on a spatially distributed stochastic wave equationAndreas Galka, Tohru Ozaki, Hiltrud Muhle, et al.
Computers in Biology and Medicine|November 19, 2005
Modelling non-stationary variance in EEG time series by state space GARCH modelKin Foon Kevin Wong, Andreas Galka, Okito Yamashita, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
Pipeline for Forward Modeling and Source Imaging of Magnetocardiographic Recordings via Spatiotemporal Kalman FilteringNawar Habboush, Laith Hamid, Michael Siniatchkin, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 21, 2005
Detection and characterization of changes of the correlation structure in multivariate time seriesMarkus Müller, Gerold Baier, Andreas Galka, et al.
Neuroimage|October 19, 2004
A solution to the dynamical inverse problem of EEG generation using spatiotemporal Kalman filteringAndreas Galka, Okito Yamashita, Tohru Ozaki, et al.
Human Brain Mapping|March 24, 2004
Recursive penalized least squares solution for dynamical inverse problems of EEG generationOkito Yamashita, Andreas Galka, Tohru Ozaki, et al.
Pageof 3

Showing results (1-10 of 30) with videos related to

Sort By:
Pageof 3
Entropy (Basel, Switzerland)|July 29, 2023
Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A ReviewFumikazu Miwakeichi, Andreas Galka
Entropy (Basel, Switzerland)|October 28, 2023
State Space Modeling of Event Count Time SeriesSidratul Moontaha, Bert Arnrich, Andreas Galka
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
Analysis of the effects of medication for the treatment of epilepsy by ensemble Iterative Extended Kalman filteringSidratul Moontaha, Andreas Galka, Thomas Meurer, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|February 1, 2013
Muscle artifact suppression using independent-component analysis and state-space modelingAlina Santillán-Guzmán, Ulrich Heute, Ulrich Stephani, et al.
Cognitive Neurodynamics|November 13, 2008
A data-driven model of the generation of human EEG based on a spatially distributed stochastic wave equationAndreas Galka, Tohru Ozaki, Hiltrud Muhle, et al.
Computers in Biology and Medicine|November 19, 2005
Modelling non-stationary variance in EEG time series by state space GARCH modelKin Foon Kevin Wong, Andreas Galka, Okito Yamashita, et al.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|November 17, 2018
Pipeline for Forward Modeling and Source Imaging of Magnetocardiographic Recordings via Spatiotemporal Kalman FilteringNawar Habboush, Laith Hamid, Michael Siniatchkin, et al.
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 21, 2005
Detection and characterization of changes of the correlation structure in multivariate time seriesMarkus Müller, Gerold Baier, Andreas Galka, et al.
Neuroimage|October 19, 2004
A solution to the dynamical inverse problem of EEG generation using spatiotemporal Kalman filteringAndreas Galka, Okito Yamashita, Tohru Ozaki, et al.
Human Brain Mapping|March 24, 2004
Recursive penalized least squares solution for dynamical inverse problems of EEG generationOkito Yamashita, Andreas Galka, Tohru Ozaki, et al.
Pageof 3