Date: 03 Oct 2005

Asymptotic study of estimation problems with small observation noise

* Final gross prices may vary according to local VAT.

Get Access


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.