Publication | Open Access
Stability and uniform approximation of nonlinear filters using the Hilbert metric and application to particle filters
145
Citations
16
References
2004
Year
Nonlinear FilteringEngineeringUniform ApproximationStochastic AnalysisFunctional AnalysisOptimal FilterState EstimationFiltering TechniqueHidden Markov ModelDigital FilterApproximation TheoryNonlinear Signal ProcessingProbability TheoryMarkov KernelInteracting Particle SystemOptimal Filter W.r.tFilter DesignInteracting Particle FilterNonlinear Filters
We study the stability of the optimal filter w.r.t. its initial condition and w.r.t. the model for the hidden state and the observations in a general hidden Markov model, using the Hilbert projective metric. These stability results are then used to prove, under some mixing assumption, the uniform convergence to the optimal filter of several particle filters, such as the interacting particle filter and some other original particle filters.
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