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Lilia Langar

Researcher at University of Grenoble

Publications -  4
Citations -  231

Lilia Langar is an academic researcher from University of Grenoble. The author has contributed to research in topics: Iteratively reweighted least squares & Recursive least squares filter. The author has an hindex of 2, co-authored 3 publications receiving 118 citations. Previous affiliations of Lilia Langar include Centre Hospitalier Universitaire de Grenoble.

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Recursive Exponentially Weighted N-way Partial Least Squares Regression with Recursive-Validation of Hyper-Parameters in Brain-Computer Interface Applications

TL;DR: A tensor-input/tensor-output Recursive Exponentially Weighted N-Way Partial Least Squares regression algorithm is proposed for high dimension multi-way (tensor) data treatment and adaptive modeling of complex processes in real-time.
Journal ArticleDOI

Space-Time-Frequency Multi-Sensor Analysis for Motor Cortex Localization Using Magnetoencephalography.

TL;DR: A regression-based multi-sensor space–time–frequency analysis (MSA) approach, which integrates co-localized sensors and/or multi-frequency information, is proposed and shows that the MSA approach provides good localization performance when compared to wMNE and statistically significant improvement of robustness against ill-defined trigger.