Abstract
We consider a piecewise linear filtering problem with small observation noise. In two different situations we construct an approximate finite-dimensional filter based on several Kalman-Bucy filters running in parallel and a procedure of tests. In the first case our work generalizes some results of Fleminget al. to more general piecewise linear dynamics.
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Références
R. F. Bass and E. Pardoux (1987), Uniqueness for diffusions with piecewise constant coefficients, Probab. Theory Related Fields, 76:557–572.
A. Bensoussan (1987), On some approximation techniques in nonlinear filtering, Stochastic Differential Systems, Stochastic Control and Applications, W. H. Flemming and P. L. Lions, eds., IMA, vol. 10, Springer-Verlag, New York, pp. 17–31.
M. Chaleyat-Maurel and D. Michel (1984), Des résultats de non existence de filtre de dimension finie, Stochastics, 13:83–102.
N. El Karoui and M. Chaleyat-Maurel (1978), Un problème de réflexion et ses applications au temps local et aux équations différentielles stochastiques sur ℝ, cas continu, Astérisque, 52–53:117–144.
W. H. Fleming, D. Ji, and E. Pardoux (1988), Piecewise linear filtering with small observation noise, Proc. 8th INRIA Conf. on Analysis and Optimization of Systems, Lecture Notes in Control and Information Science, vol. 111, Springer-Verlag, Berlin, pp. 725–739.
W. H. Fleming, D. Ji, P. Salame, and Q. Zhang (1991), Piecewise monotone filtering in discrete time with small observation noise, IEEE Trans. Automat. Control, 36:1181–1186.
W. H. Fleming and E. Pardoux (1989), Piecewise monotone filtering with small observation noise, SIAM J. Control Optim., 20:1156–1181.
M. Fujisaki, G. Kallianpur, and H. Kunita (1972), Stochastic differential equations for the nonlinear filtering problem, Osaka J. Math., 9:19–44.
A. H. Jazwinski (1970), Stochastic Processes and Filtering Theory, Academic Press, New York.
D. Ji (1987), Nonlinear Filtering with Small Observation Noise, Ph.D. Thesis, Brown University.
R. E. Kalman and R. S. Bucy (1961), New results in linear filtering and prediction theory, J. Basic Engrg ASME, 83:95–108.
R. Katzur, B. Z. Bobrovsky, and Z. Schuss (1984), Asymptotic analysis of the optimal filtering problem for one-dimensional diffusions measured in a low noise channel, I, II, SIAM J. Appl. Math., 44:591–604, and 44:1176–1191.
H. J. Kushner (1964), On the differential equations satisfied by the conditional probability densities of Markov processes, SIAM J. Control, 2:106–119.
F. Le Gland (1981), Estimation de paramètres dans les processus stochastiques, en observation incomplète—Application à un problème de radio-astronomie, Thèse de Docteur-Ingenieur, Université Paris IX-Dauphine.
R. Ch. Liptzer and A. N. Shyriaev (1977), Statistics of Random Processes, Vols. I-II, Springer-Verlag, New York.
P. Milheiro de Oliveira (1990), Etudes asymptotiques en filtrage non linéaire avec petit bruit d'observation, Thèse, Université de Provence.
P. Milheiro de Oliveira and M. C. Roubaud (1991), Filtrage linéaire par morceaux d'un système en temps discret avec petit bruit d'observation, Rapport 1451, INRIA.
D. Ocone and E. Pardoux (1989), A Lie-algebraic criterion for nonexistence of finite-dimensionally computable filters, Proc. 3rd Trente Conf. on SPDEs II, G. Da Prato and L. Tubaro, eds., Lecture Notes in Mathematics, No. 1390, Springer-Verlag, Berlin.
E. Pardoux and M. C. Roubaud (1991), Finite-dimensional approximate filter in case of high signal-to-noise ratio, Stochastic Analysis, E. Merzbach, A. Shwartz, and E. Mayer-Wolf, eds., Academic Press, New York, pp. 433–448.
J. Picard (1986), Nonlinear filtering of one-dimensional diffusions in the case of a high signal-to-noise ratio, SIAM J. Appl. Math., 46:1098–1125.
J. Picard (1987), Asymptotic study of estimation problems with small observation noise, in Stochastic Modelling and Filtering, Lecture Notes in Control and Information Science, Vol. 91, Springer-Verlag, Berlin.
J. Picard (1991), Efficiency of the extended Kalman filter for nonlinear systems with small noise, SIAM J. Appl. Math., 51:843–885.
M. C. Roubaud (1990), Filtrage linéaire par morçeaux avec petit bruit d'observation, Thèse, Université de Provence.
W. M. Wonham (1985), Linear Multivariable Control: a Geometric Approach, 3rd edn. Springer-Verlag, New York.
M. Zakai (1969), On the optimal filtering of diffusion processes, Z. Wahrsch. Verw. Gebiete, 11:230–243.
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Roubaud, M.C. Filtrage linéaire par morceaux avec petit bruit d'observation. Appl Math Optim 32, 163–194 (1995). https://doi.org/10.1007/BF01185229
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DOI: https://doi.org/10.1007/BF01185229
Mots-clés
- Filtrage linéaire par morceaux
- Petit bruit d'observation
- Filtres approchés
- Filtre de Kalman-Bucy
- Test du rapport de vraisemblance