TY  - JOUR
ID  - iiasa14150
UR  - https://pure.iiasa.ac.at/id/eprint/14150/
IS  - 2
A1  - Kurzhanski, A.
N2  - This paper considers estimating the state of a discrete-time linear system in which the values of an unobserved disturbance process are only known to lie in certain prescribed sets. By introducing additional stochastic disturbances it is shown that this problem can be approximated to arbitrarily high accuracy by the solution of a Kalman filtering problem
VL  - 23
TI  - On stochastic filtering approximations of estimation problems for systems with uncertainty?
AV  - none
EP  - 130
Y1  - 1988///
PB  - Taylor and Francis
JF  - Stochastics
KW  - State estimation
KW  -  multistage linear system
KW  -  geometric constraints
KW  -  convex analysis
KW  -  Kalman filter
SN  - 0090-9491
SP  - 109
ER  -