Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
We consider the problem of how the CNS learns to control dynamics of a mechanical system. By using a paradigm where a subject's hand interacts with a virtual mechanical envir...
This paper discusses novel research conducted to study the direct impact of learner's affective changes on the value of a well established EEG-mental engagement index. An acq...
Maher Chaouachi, Pierre Chalfoun, Imene Jraidi, Cl...
Abstract. In this paper, we propose a method for blind source separation (BSS) of convolutive audio recordings with short blocks of stationary sources, i.e. dynamically changing so...
In this paper we address the problem of producing an enlarged picture from a given digital image (zooming). We propose a method that tries to take into account information about d...
Sebastiano Battiato, Giovanni Gallo, Filippo Stanc...