Robust behavior of multi-band paradigm

Colloque avec actes et comité de lecture.In this paper, we have gathered new results obtained with our Multi-Band system on the TIMIT database corrupted by additive noise. The robustness of the Multi-Band system to several kinds of noise is studied in details. The system is robust to spectral-limited noise, as it has already been shown in previous papers, but it is also robust to broad-spectral noise as long as the full-band is added as an additionnal stream to the Multi-Band system. A more robust version of this system is then obtained when training the recombination module in white noise. Thus, robustness to other kinds of noise is increased. Finally, we present the first results obtained with a new training algorithm which globally optimizes the Multi-Band system. Regarding the robustness of the method, these preliminary results are encouraging

A Statistical Approach to the Alignment of fMRI Data

Multi-subject functional Magnetic Resonance Image studies are critical. The anatomical and functional structure varies across subjects, so the image alignment is necessary. We define a probabilistic model to describe functional alignment. Imposing a prior distribution, as the matrix Fisher Von Mises distribution, of the orthogonal transformation parameter, the anatomical information is embedded in the estimation of the parameters, i.e., penalizing the combination of spatially distant voxels. Real applications show an improvement in the classification and interpretability of the results compared to various functional alignment methods

A comparison of the CAR and DAGAR spatial random effects models with an application to diabetics rate estimation in Belgium

When hierarchically modelling an epidemiological phenomenon on a finite collection of sites in space, one must always take a latent spatial effect into account in order to capture the correlation structure that links the phenomenon to the territory. In this work, we compare two autoregressive spatial models that can be used for this purpose: the classical CAR model and the more recent DAGAR model. Differently from the former, the latter has a desirable property: its ρ parameter can be naturally interpreted as the average neighbor pair correlation and, in addition, this parameter can be directly estimated when the effect is modelled using a DAGAR rather than a CAR structure. As an application, we model the diabetics rate in Belgium in 2014 and show the adequacy of these models in predicting the response variable when no covariates are available

Energy: A continuing bibliography with indexes, issue 20

A bibliography is presented which lists 1250 reports, articles, and other documents introduced into the NASA Scientific and Technical Information System from October 1, 1978 through December 31, 1978