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Stochastic optimal estimation and control theories have been used to estimate the states and to derive the control laws, respectively.
To asses the retrived profiles, and for retrievals with the method of optimal estimation, a-priori knowledge together with related error estimates is furthermore needed.
The apparent decrease in the learning rate was consistent with a statistical model of optimal estimation that began relatively unsure, but became progressively certain of its estimates.
The problem of designing such estimators for general nonlinear systems is solved by searching for optimal estimation functions.
A state estimator based on an Extended Kalman filter is introduced to guarantee optimal estimation results for the angular velocity.
Genoni, M. G. et al. Optimal estimation of joint parameters in phase space.
The retrieval is based on the optimal estimation method.
Optimal estimation of the soil uptake rate of molecular hydrogen from the Advanced Global Atmospheric Gases Experiment and other measurements.
This includes problems with regularization where optimal estimation allows us to perform online segmentation of streaming data.
Two parameters, initial eccentricity and ballistic coefficient, are chosen for optimal estimation.
N. Shah, S. Balakrishnan, and M. Wainwright, "A Permutation-based Model for Crowd Labeling: Optimal Estimation and Robustness," UC Berkeley, June 2016.
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