Second, computers are highly efficient at matrix calculations. Anal. H. Gianin , Representation of the penalty term of dynamic concave utilities , Finance Stoch. de Souzaand M.
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Google Scholar5. 95 — 108 . F. S. S. 1016/j.
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CrossrefGoogle Scholar25. The state of the target system refers to the ground truth (yet hidden) system configuration of interest, which is represented as a vector of real numbers. Simply running the filter without considering the reliability of this estimate does not take into account this additional source of statistical uncertainty. K. 1740 — 1786 .
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H. Together with the linear-quadratic regulator (LQR), the Kalman filter solves the linear–quadratic–Gaussian control problem (LQG). Bain and D. Issue Date: September 1979DOI: https://doi. We start at the last time step and proceed backward in time using the following recursive equations:
where
x
k
k
{\displaystyle \mathbf {x} _{k\mid k}}
is the a-posteriori state estimate of timestep
k
{\displaystyle k}
and
x
k
+
1
k
{\displaystyle \mathbf {x} _{k+1\mid k}}
is the a-priori state estimate of timestep
k
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1
{\displaystyle k+1}
.
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The design of
W
{\displaystyle \mathbf {W} }
remains an open question. .