In this study, we investigate online Bayesian estimation of the measurement noise density of a given state space model using particle filters and Dirichlet process mixtures. Diri...
We define a new reduced model to represent coloured images. We propose to use two components for a full definition of a colour instead of three. To that end we take advantage of...
Frederic Garcia, Djamila Aouada, Bruno Mirbach, Bj...
In high quality imaging even tiny distortions as small as a single pixel are visible and can not be accepted. Although the production quality of CMOS image sensors is very high, f...
Recently, one of the authors has reported that the amount of generated musical noise is strongly correlated with higher-order statistics of the power spectra. On the basis of this...
This paper investigates a Bayesian model and a Markov chain Monte Carlo (MCMC) algorithm for gene factor analysis. Each sample in the dataset is decomposed as a linear combination...
Cecile Bazot, Nicolas Dobigeon, Jean-Yves Tournere...
We study the scenario of pixel-domain distributed video coding for noisy transmission environments and propose a method to allocate the available rate between source coding and ch...
We consider the problem of tracking a maneuvering target in urban terrain with high clutter. Although multipath has been previously exploited to improve target tracking in complex...
Bhavana Chakraborty, Jun Jason Zhang, Antonia Papa...
We introduce a simple approach to segment in homogeneous phases a long-duration record of locomotion data consisting of body segment acceleration and foot pressure information onl...
Maud Pasquier, Bernard Espiau, Christine Azevedo-C...
To harvest the potential of multi-channel noise reduction methods, it is crucial to have an accurate estimate of the noise correlation matrix. Existing algorithms either assume sp...
This paper studies system identification of ARMA models whose outputs are subject to finite-level quantization and random packet dropouts. A simple adaptive quantizer and the co...