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Efficient particle filtering through residual nudging
Efficient particle filtering residual nudging
2013/5/2
We introduce an auxiliary technique, called residual nudging, to the particle filter to enhance its performance in cases that it performs poorly. The main idea of residual nudging is to monitor, and i...
Top-down particle filtering for Bayesian decision trees
Top-down particle filtering Bayesian decision trees
2013/4/27
Decision tree learning is a popular approach for classification and regression in machine learning and statistics, and Bayesian formulations---which introduce a prior distribution over decision trees,...
Particle filtering in high-dimensional chaotic systems
particle filtering in high dimensions chaotic systems Lorenz’96 nonlinear filtering dimensional reduction homogenization
2012/4/20
We present an efficient particle filtering algorithm for multiscale systems, that is adapted for simple atmospheric dynamics models which are inherently chaotic. Particle filters represent the posteri...
Application of Girsanov Theorem to Particle Filtering of Discretely Observed Continuous-Time Non-Linear Systems
Girsanov theorem particle ltering continuous-discrete ltering
2009/9/22
This article considers the application of particle ltering to continuous-
discrete optimal ltering problems, where the system model is a stochastic dier-
ential equation, and noisy measurements of t...
Application of Girsanov Theorem to Particle Filtering of Discretely Observed Continuous-Time Non-Linear Systems
Girsanov theorem particle filtering continuous-discrete filtering
2010/4/29
This article considers the application of particle filtering to continuousdiscrete
optimal filtering problems, where the system model is a stochastic differential
equation, and noisy measurements of...