Nous considérons un processus gaussien symétrique à valeurs matricielles Y(n)=(Y(n)(t);t≥0) et son des mesures spectrales empiriques μ(n)=(μt(n);t≥0). Sous conditions assez faibles sur la fonction de covariance Y(n) nous trouvons une expression explicite pour loi limite ZF(n):=((Zf 1(n)(t),…,Zf r(n)(t));t≥0), où F=(f1,…,fr), r≥1, avec chaque composant appartenant grande classe fonctions test, Z...

This study examines the use of Gaussian process (GP) regression for sound field reconstruction. GPs enable reconstruction a from limited set observations based on covariance function (a kernel) that models spatial correlation between points in field. Significantly, approach makes it possible to quantify uncertainty closed form. In this study, relation and classical methods linear is examined an...

We consider the optimal transport problem between multivariate Gaussian stationary stochastic processes. The transportation effort is variance of filtered discrepancy process. main contribution this article to show that corresponding solution leads a weighted Hellinger distance power spectral densities. Then, we propose estimation approach in case indirect measurements, which based on distance.