Variational Bayes Phase Tracking for Correlated Dual-Frequency Measurements with Slow Dynamics

We consider the problem of estimating the absolute phase of a noisy signal when this latter consists of correlated dual-frequency measurements. This scenario may arise in many application areas such as global navigation satellite system (GNSS). In this paper, we assume a slow varying phase and propose accordingly a Bayesian filtering technique that makes use of the frequency diversity. More specifically, the method results from a variational Bayes approximation and belongs to the class of nonlinear filters. Numerical simulations are performed to assess the performance of the tracking technique especially in terms of mean square error and cycle-slip rate. Comparison with a more conventional approach, namely a Gaussian sum estimator, shows substantial improvements when the signal-to-noise ratio and/or the correlation of the measurements are low

Mise en place d'un atlas d'images radiographiques et échographiques pathologiques du rat domestique

Les examens complémentaires, notamment les examens d’imagerie, se démocratisent en médecine des NAC, mais peu de ressources existent pour l’analyse et l’interprétation des images. Il s’agit pourtant d’outils modernes qui sont d’une grande utilité pour le diagnostic chez les animaux de compagnie. L’objectif de ce travail est de rappeler le fonctionnement des appareils de radiographie et d’échographie, de présenter l’anatomie particulière du rat domestique Rattus norvegicus et ses conséquences sur l’imagerie physiologique de cette espèce, et de fournir un atlas en ligne d’images radiographiques et échographiques pathologiques du rat domestique, comme support pratique et pédagogique à destination des praticiens et des étudiants vétérinaires comme support pour leur formation

On the Equivalence between Kalman Filter at Steady State and DPLL

Fundamental results in the literature previously showed that a class of Kalman filter converges to a digital phase lock loop (DPLL) structure at the second and third order. We generalize these results at any order and give the closed-form linear relation, and its inverse, between the steady-state Kalman gains and the loop filter constants. Both relations are simple and only involve Stirling numbers of the first and second kind. This new result may help in a deeper understanding of the equivalence between Kalman filter and DPLL and be of practical interest in high dynamic scenarios

Analysis of a large fMRI cohort: Statistical and methodological issues for group analyses.

International audienceThe aim of group fMRI studies is to relate contrasts of tasks or stimuli to regional brain activity increases. These studies typically involve 10 to 16 subjects. The average regional activity statistical significance is assessed using the subject to subject variability of the effect (random effects analyses). Because of the relatively small number of subjects included, the sensitivity and reliability of these analyses is questionable and hard to investigate. In this work, we use a very large number of subject (more than 80) to investigate this issue. We take advantage of this large cohort to study the statistical properties of the inter-subject activity and focus on the notion of reproducibility by bootstrapping. We asked simple but important methodological questions: Is there, from the point of view of reliability, an optimal statistical threshold for activity maps? How many subjects should be included in group studies? What method should be preferred for inference? Our results suggest that i) optimal thresholds can indeed be found, and are rather lower than usual corrected for multiple comparison thresholds, ii) 20 subjects or more should be included in functional neuroimaging studies in order to have sufficient reliability, iii) non-parametric significance assessment should be preferred to parametric methods, iv) cluster-level thresholding is more reliable than voxel-based thresholding, and v) mixed effects tests are much more reliable than random effects tests. Moreover, our study shows that inter-subject variability plays a prominent role in the relatively low sensitivity and reliability of group studies

Robust estimation of high-order phase dynamics using Variational Bayes inference

Cycle slips strongly impact the performance of phase tracking algorithm leading, in the worst case, to a permanent loss of lock of the signal. In this paper, we propose a new nonlinear phase estimator to obtain more robust tracks. The latter stems from a Variational Bayes (VB) approximation used within the optimal Bayesian filtering formulation in case of high-order phase dynamics. A comparison with a more conventional technique, namely a Kalman filter based PLL (Phase Lock Loop), is performed in terms of mean square error of the phase estimate and mean time to first slip. Results show that the proposed method outperforms the conventional linear filter with respect to both metrics, especially at low signal-to-noise ratio

Rigid Point-Surface Registration using Oriented Points and an EM Variant of ICP for Computer Guided Oral Implantology

We investigate in this research report the rigid registration of a set of points with a surface for computer-guided oral implants surgery. We first formulate the Iterative Closest Point (ICP) algorithm as a Maximum Likelihood (ML) estimation of the transformation and the matches. Then, considering matches as a hidden random variable, we show that the ML estimatio- n of the transformation alone leads to a criterion efficiently solved using an Expectation-Maximisation (EM) algorithm. This algorithm implies a new parameter, based on the standard-deviation of the noise on points position. We demonstrate that, for small values, the algorithm behaves like the accurate ICP, while, for high values, the algorithm robustly aligns the barycenter and inertia moments. Finaly, this parameter is decreased using an annealing scheme, which can be seen as a kind of multi-scale scheme. We present besides an efficient way to use oriented points - like surface points with their normals - instead of points with ICP and EM algorithms. The experimental section provides evidences that the EM algorithm is far more robust and more accurate than ICP and reaches a global accuracy of 0.2 mm with computation times compatible with a per-operative system. Another important property is that the criterion analysis enables an easy distinction between correct results and false postives

Soft-Error Rate of Advanced SRAM Memories: Modeling and Monte Carlo Simulation

International audienc

Robust GNSS phase tracking in case of slow dynamics using variational Bayes inference

For a precise GNSS (Global Navigation Satellite System) positioning, carrier phase measurements are required. However, cycle slipping in classical phase locked loop (PLL) can lead to a local or permanent loss of lock. To address this problem, we propose a robust nonlinear filter for carrier phase tracking based on Variational Bayes (VB) inference. So far, the algorithm is designed only for slow phase dynamics (i.e., first order loop). Interestingly, the estimator update equation can be expressed in closed form. Performance of our algorithm is assessed on synthetic and experimental GNSS data and compared to that of conventional PLL-based techniques. Results show that the proposed method brings significant improvement in terms of cycle slipping

Sex-related differences in endothelial function and blood viscosity in the elderly population

Elderly represents a growing population and cardiovascular diseases (CVD) is one of the leading causes of mortality in this population. Sex differences are involved in CVD with middle-aged males being at higher risk than females. After menopause, females are no longer protected by hormones and the role of sex on cardiovascular parameters involved in CVD, such as endothelial function and blood viscosity, is still unclear. The purpose of this study was to investigate the effect of sex on endothelial function, blood viscosity and CVD in elderly. Clinical investigation and blood analyses were performed on 182 (93 females and 89 males) elderly participants (mean age: 75.83 ± 1.22). Health status of participants were classified. Sex differences in endothelial function, blood viscosity, high density lipoprotein (HDL), hematocrit, and red blood cell (RBC) aggregation were assessed. CVD prevalence was higher in males (27.0%) than in females (5.4%) (p < 0.001). Females had higher vasoreactivity (p = 0.014) and HDL (p < 0.001) level than males. Blood viscosity was higher in males than in females at any shear rate (p < 0.001). Hematocrit was greater in males than in females (p < 0.001) while RBC aggregation did not differ between the two populations. To conclude, females have less CVD than age-matched males that might be due to their greater vascular function and lower blood viscosity