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Exponential Forgetting and Geometric Ergodicity in Hidden Markov Models

• François Le Gland, Laurent Mevel
• MCSS
• 2000

We consider a hidden Markov model with multidimensional observations, and with misspecification, i.e. the assumed coefficients (transition probability matrix, and observation conditional densities)… (More)

Genetic Genealogical Models in Rare Event Analysis

• Frédéric Cérou, Pierre Del Moral, François Le Gland, Pascal Lezaud
• 2006

We present in this article a genetic type interacting particle systems algorithm and a genealogical model for estimating a class of rare events arising in physics and network analysis. We represent… (More)

Large Sample Asymptotics for the Ensemble Kalman Filter

• François Le Gland, Valérie Monbet
• 2009

The ensemble Kalman lter (EnKF) has been proposed as a Monte Carlo, derivative free, alternative to the extended Kalman lter, and is now widely used in sequential data assimilation, where state… (More)

Geometric Ergodicity in Hidden Markov Models

• François Le Gland
• 1996

We consider an hidden Markov model with multidimensional observations, and with misspecii-cation, i.e. the assumed coeecients (transition probability matrix, and observation conditional densities)… (More)

Multidimensional Laplace formulas for nonlinear Bayesian estimation

• Paul Bui Quang, Christian Musso, François Le Gland
• 2012 Proceedings of the 20th European Signal…
• 2012

The Laplace method and Monte Carlo methods are techniques to approximate integrals which are useful in nonlinear Bayesian computation. When the model is one-dimensional, Laplace formulas to compute… (More)

Basic Properties of the Projective Product with Application to Products of Column-Allowable Nonnegative Matrices

• François Le Gland, Laurent Mevel
• MCSS
• 2000

We use basic properties of the projective product, to obtain exponential bounds for the Lipschitz constant associated with the projective product of column{allowable nonnegative matrices. We obtain… (More)

Information fusion for indoor localization

• Pierre Blanchart, Liyun He, François Le Gland
• 2009 12th International Conference on Information…
• 2009

This paper describes a fusion approach to the problem of indoor localization of a pedestrian user, in which PNS measurements, cartographic constraints and ranging or proximity beacon measurements are… (More)

An overview of importance splitting for rare event simulation

• Jérôme Morio, Rudy Pastel, François Le Gland
• 2011

Monte Carlo simulations are a classical tool to analyse physical systems. When unlikely events are to be simulated, the importance sampling technique is often used instead of Monte Carlo. Importance… (More)

A PARTICLE IMPLEMENTATION OF THE RECURSIVE MLE FOR PARTIALLY OBSERVED DIFFUSIONS

• Arnaud Guyader, François Le Gland, Nadia Oudjane
• 2003

In this paper, the problem of identifying a hidden M arkov model (HMM) with general state space, e.g. a partially observed diffusion pr cess, is considered. A particle implementation of the recursive… (More)

An insight into the issue of dimensionality in particle filtering

• Paul Bui Quang, Christian Musso, François Le Gland
• 2010 13th International Conference on Information…
• 2010

Particle filtering is a widely used Monte Carlo method to approximate the posterior density in non-linear filtering. Unlike the Kalman filter, the particle filter deals with non-linearity,… (More)

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