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Loi gamma-normale

Publications associées (86)

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A Novel Bayesian Impulse Radio Ultra-WideBand Ranging Algorithm

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We consider the problem of ranging with Impulse Radio (IR) Ultra-WideBand (UWB) radio under weak Line Of Sight (LOS) environments and additive Gaussian noise. We use a Bayesian approach where the prior distribution of the channel follows the IEEE 802.15.4a ...

IEEE2009

One Step Impulse Radio Ultra-WideBand Positioning Algorithm

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We consider the problem of positioning estimation with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths and additive Gaussian noise environments. Most popular positioning algorithms first estimate certain parameters (such as time of arr ...

IEEE2009

4th International Conference on Construction Materials

The resistance as well as strain hardening and softening properties of UHPFRC depend on the type of matrix and mainly on the fibre dosage and final distribution and orientation in the element. The strength and deformability distribution in a thin UHPFRC pa ...

Japan Concrete Institute (JCI) Japan Society of Civil engineers (JSCE) Canadian society for Civil engineering (CSCE) ConMat'092009

Novel Algorithms on Impulse Radio Ultra-WideBand Ranging

Jean-Yves Le Boudec, John Farserotu, Hai Zhan

We consider the problem of ranging with impulse radio (IR) ultra-wideband (UWB) radio under dense multipaths propagation environments and additive Gaussian noise. We propose a Bayesian detection algorithm where the prior distribution of the channel follows ...

IEEE2009

On the representation of droplet coalescence and autoconversion: Evaluation using ambient cloud droplet size distributions

Athanasios Nenes

In this study, we evaluate eight autoconversion parameterizations against integration of the Kinetic Collection Equation (KCE) for cloud size distributions measured during the NASA CRYSTAL-FACE and CSTRIPE campaigns. KCE calculations are done using both th ...

Blackwell Publishing Ltd2009

On the calibration of hydrological models in ungauged basins: A framework for integrating hard and soft hydrological information

Bettina Schaefli

This paper presents a calibration framework based on the generalized likelihood uncertainty estimation (GLUE) that can be used to condition hydrological model parameter distributions in scarcely gauged river basins, where data is uncertain, intermittent or ...

American Geophysical Union2009

A MAP Approach to Noise Compensation of Speech

Philip Neil Garner

We show that estimation of parameters for the popular Gaussian model of speech in noise can be regularised in a Bayesian sense by use of simple prior distributions. For two example prior distributions, we show that the marginal distribution of the uncorrup ...

Idiap2009

Saddlepoint approximation for mixture models

Anthony Christopher Davison

Two-component mixture distributions with one component a point mass and the other a continuous density may be used as priors for Bayesian inference when sparse representation of an underlying signal is required. We show how saddlepoint approximation in suc ...

2009

Predicting spacial similarity of freshwater fish biodiversity

Andrea Rinaldo, Mihaela Marian

A major issue in modern ecology is to understand how ecological complexity at broad scales is regulated by mechanisms operating at the organismic level. What specific underlying processes are essential for a macroecological pattern to emerge? Here, we anal ...

2009

Bayesian Inference for Spiking Neuron Models with a Sparsity Prior

Matthias Seeger, Matthias Bethge

Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the expectation propagation algorithm, we are able to approximate the full poster ...

2008