Abstract
We consider a nonlinear filtering problem, whose dynamics is “piecewise linear”. We construct a suboptimal filter consisting of a finite number of Kalman filters working in parallel, and exchanging their information at times δ, 2δ, 3δ …. We establish the convergence of that filter towards the optimal filter, as δ → 0.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
R.F. Bass, E. Pardoux, Uniqueness for diffusions with piecewise constant coefficients, submitted to Probability Theory and Related Fields.
V.E. Benĕs, I. Karatzas, Filtering for piece-wise linear drift and observation, Proc. 20th IEEE CDC, (1981), pp. 583–589.
V.E. Benĕs, I. Karatzas, Estimation and control of linear, partially observed systems with non-gaussian initial distribution, Stoch. Proc. and Applic., 14 (1983), pp. 233–298.
K.L. Chung, R.J. Williams, Introduction to stochastic integration, Birkhäuser.
G. Kallianpur, Stochastic filtering theory, Springer-Verlag.
A. Makowski, Filtering formulae for partially observed linear systems with non gaussian initial conditions, Stochastics, 16 (1986), pp. 1–24.
J. Picard, Robustesse de la solution des problèmes de filtrage avec bruit blanc indépendant, Stochastics, 13 (1986), pp. 229–245.
C. Savona, Filtrage linéaire par morceaux, Thesis, Univ. de Provence, 1986.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 1988 Springer-Verlag New York Inc.
About this paper
Cite this paper
Pardoux, E., Savona, C. (1988). Piecewise Linear Filtering. In: Fleming, W., Lions, PL. (eds) Stochastic Differential Systems, Stochastic Control Theory and Applications. The IMA Volumes in Mathematics and Its Applications, vol 10. Springer, New York, NY. https://doi.org/10.1007/978-1-4613-8762-6_26
Download citation
DOI: https://doi.org/10.1007/978-1-4613-8762-6_26
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4613-8764-0
Online ISBN: 978-1-4613-8762-6
eBook Packages: Springer Book Archive