IEEE Transactions on Automatic Control · 1964 · 473 citations · 8 references
State EstimationNonlinear System IdentificationNoisy Dynamic SystemsParameter IdentificationEngineeringState ObserverUncertainty QuantificationState VariablesDynamic Programming FormulationProcess ControlNoiseSystems EngineeringLinear ProblemObserver DesignSystem IdentificationSignal Processing
The problem of estimating state variables and parameters is considered for discrete-time systems in the presence of random disturbances and measurement noise. The solution of the linear problem is given and an approximation technique is developed for nonlinear systems. A dynamic programming formulation of the estimation problem is also developed.
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The Mathematical Theory of Optimal Processes.
E. K. Blum, Pontryagin, Boltyanskii et al. · American Mathematical Monthly · 1963 · 4.3K citations
Mathematical Economics, Probability Theory, Optimal Processes