E. Giraldo-Suárez

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We present a novel iterative regularized algorithm (IRA) for neural activity reconstruction that explicitly includes spatiotemporal constraints, performing a trade-off between space and time resolutions. For improving the spatial accuracy provided by electroencephalography (EEG) signals, we explore a basis set that describes the smooth, localized areas of(More)
This article presents an estimation method of neuronal activity into the brain using a Kalman smoother approach that takes into account in the solution of the inverse problem the dynamic variability of the time series. This method is applied over a realistic head model calculated with the boundary element method. A comparative analysis for the dynamic(More)
Identificación de modelos dinámicos no lineales variantes en el tiempo en problemas mal condicionados correspondientes a la estimación de la actividad neuronal a partir de señales EEG Identificación de modelos dinámicos no lineales variantes en el tiempo en problemas mal condicionados correspondientes a la estimación de la actividad neuronal a partir de(More)
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