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Extraction of a Source from Multichannel Data Using Sparse Decomposition
ICA Blind source separation Sparse representation Wavelets EEG MEG
2010/1/7
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decomposition of a source in ...
Extraction of a Source from Multichannel Data Using Sparse Decomposition
ICA Blind source separation Sparse representation Wavelets EEG MEG
2010/1/7
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decomposition of a source in ...
Complete Sets of Radiating and Nonradiating Parts of a Source and Their Fields with Applications in Inverse Scattering Limited-Angle Problems
Inverse Scattering Limited-Angle Problems Source
2009/9/8
Many algorithms applied in inverse scattering problems use source-field systems instead of the direct computation of the unknown scatterer. It is well known that the resulting source problem does not ...
A Monte-Carlo-Based Network Method for Source Positioning in Bioluminescence Tomography
Monte-Carlo-Based Network Bioluminescence Tomography
2009/9/7
We present an approach based on the improved Levenberg Marquardt (LM) algorithm of backpropagation (BP) neural network to estimate the light source position in bioluminescent imaging. For solving the ...
Current computed tomography (CT) scanners, including micro-CT scanners, utilize a point x-ray source. As we target higher and higher spatial resolutions, the reduced x-ray focal spot size limits the t...
Open source model for generating RR intervals in atrial fibrillation and beyond
Open source model RR intervals atrial fibrillation and beyond
2010/2/26
Background
Realistic modeling of cardiac inter-beat (RR) intervals is highly desirable for basic research in cardiac electrophysiology, clinical management of heart diseases, and developing signal pr...
Influence of head models on neuromagnetic fields and inverse source localizations
head models neuromagnetic fields inverse source localizations
2010/2/26
The reference model (Model 1), as expected, performed best in localizing the sources in the motor cortex area. The Model 3 performed the worst. The mean source localization errors (MLEs) of the Model ...
Effects of dipole position, orientation and noise on the accuracy of EEG source localization
dipole position orientation and noise EEG source localization
2010/3/1
It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increa...