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Communication Dans Un Congrès Année : 2011

Kalman filtering approximations in triplet Markov Gaussian switching models

Résumé

We consider a general triplet Markov Gaussian linear system (X, R, Y), where X is hidden continuous, R is hidden discrete, and Y is observed continuous. Exact Kalman filter (KF) is not workable and two approximations are considered in the paper. The classical one consists of particle filtering, which is a new extension of the classical method we propose. Another new method we propose consists of replacing the model by a simpler one, in which (R, Y) is Markovian and in which exact KF can be performed. We show the interest of our method via experiments
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Dates et versions

hal-01347978 , version 1 (22-07-2016)

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Noufel Abbassi, Dalila Benboudjema, Wojciech Pieczynski. Kalman filtering approximations in triplet Markov Gaussian switching models. SSP 2011 : Statistical Signal Processing Workshop, Jun 2011, Nice, France. pp.77 - 80, ⟨10.1109/SSP.2011.5967820⟩. ⟨hal-01347978⟩
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