Bayesian joint estimation of the multifractality parameter of image patches using gamma Markov Random Field priors

Turbidity time series were used to test application of Autoregressive Moving Average model (ARMA) in order to obtain the relationship between turbidity values at

De plus (même si dans le modèle allemand c’est la nation qui reste détentrice de la souveraineté), les modèles allemands et suisses sont compatibles avec une large

However, this measurement requires the knowledge of accurate values of the frequency detuning F inj (optical frequency diference between the master and slave lasers) and the

Time evolution of the amplitudes of two incident surface-mode waves wavenumber k1 , k2 and the resonance generated internal-mode wave wavenumber kr undergoing resonant

four, and five. Within this production plan are lower-level problems involving disaggregation of the period production plan within a fixed plant configuration, such as work

The goals of this paper are the following: (1) we characterize the evolution of high-end wine prices during the last decade, (2) we study long-run, short-run and causality

multivariate image by gamma Markov random field joint priors, accounting for the assump- tion that multifractal properties evolve smoothly in privileged (temporal/spectral,

In contrast, considering the mix- ing filter as a latent variable as proposed in the present study enables to directly define Ra,j,f as a full-rank matrix with (5), while keeping