Zusammenfassung
We propose an algorithm, based on blind source separation methods, for blindly estimating the sensor characteristics of a multi-sensor network, whose structure is also unknown. From the observed sensor outputs, the non-linearities are recovered using a well-known Gaussianization procedure. The underlying sources are then reconstructed using spatial decorrelation. Application of this robust ...
Zusammenfassung
We propose an algorithm, based on blind source separation methods, for blindly estimating the sensor characteristics of a multi-sensor network, whose structure is also unknown. From the observed sensor outputs, the non-linearities are recovered using a well-known Gaussianization procedure. The underlying sources are then reconstructed using spatial decorrelation. Application of this robust algorithm to data sets acquired through functional magnetic resonance imaging (fMRI) lead to detecting a distinctive 'bump' of the BOLD (blood oxygenation level dependent) effect at larger activations.