Asymptotic study of estimation problems with small observation noise
- Jean Picard
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In this paper, we study the nonlinear filtering of multidimensional diffusions which are measured in a low noise channel. We describe approximate filters which are solutions of stochastic differential equations driven by the observation process; upper bounds for the corresponding approximation errors are given. The proof is detailed in a particular case where the result can be improved; in particular, the efficiency of the extended Kalman filter is studied.
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- Asymptotic study of estimation problems with small observation noise
- Book Title
- Stochastic Modelling and Filtering
- Book Subtitle
- Proceedings of the IFIP-WG 7/1 Working Conference Rome, Italy, December 10–14, 1984
- pp 131-146
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- Series Title
- Lecture Notes in Control and Information Sciences
- Series Volume
- Series ISSN
- Springer Berlin Heidelberg
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