DocumentCode :
1037749
Title :
Kalman Filtering in Triplet Markov Chains
Author :
Ait-El-Fquih, Boujemaa ; Desbouvries, François
Author_Institution :
CITI, Inst. Nat. des Telecommun., Evry
Volume :
54
Issue :
8
fYear :
2006
Firstpage :
2957
Lastpage :
2963
Abstract :
Let x = {xn} nisinIN be a hidden process, y = {yn}nisinIN an observed process, and r = {rn}nisinIN some additional process. We assume that t = (x, r, y) is a (so-called "Triplet") vector Markov chain (TMC We first show that the linear TMC model encompasses and generalizes, among other models, the classical state-space systems with colored process and/or measurement noise(s). We next propose restoration Kalman-like filters for arbitrary linear Gaussian (LG) TMC
Keywords :
Gaussian processes; Kalman filters; Markov processes; arbitrary linear Gaussian TMC; classical state-space systems; colored process; linear TMC model; measurement noise; restoration Kalman-like filters; triplet vector Markov chains; Colored noise; Filtering; Hidden Markov models; Kalman filters; Noise measurement; Nonlinear filters; Probability density function; Signal processing algorithms; Signal restoration; Vectors; Bayesian signal restoration; Kalman filtering; Markovian models; hidden Markov chains; triplet Markov chains;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/TSP.2006.877651
Filename :
1658251
Link To Document :
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