Regularization for distributionally robust state estimation and prediction
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In this paper we consider reduced basis approximation and a posteriori error estimation for linear functional outputs of affinely parametrized linear and non-linear parabolic partial differential equations. The essential ingredients are Galerkin projection ...
The number of vehicles included in a metered motorway ramp or an urban signalized link at any time is valuable information for real-time control. A Kalman-Filter is employed to produce reliable estimates of this quantity based on real-time measurements of ...
This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown parameter. Thus in order to support the state estimator with prior information o ...
This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the state estimates computed by any sensor to the correct state even when constraint ...
This paper focuses on distributed state estimation using a sensor network for monitoring a linear system. In order to account for physical constraints on process states and inputs, we propose a moving horizon approach where each sensor has to solve a quadr ...
This paper presents a novel distributed estimation algorithm based on the concept of moving horizon estimation. Under weak observability conditions we prove convergence of the state estimates computed by any sensor to the correct state even when constraint ...
In a posteriori error analysis of reduced basis approximations to affinely parametrized partial differential equations, the construction of lower bounds for the coercivity and inf-sup stability constants is essential. In [Huynh et al., C. R. Acad. Sci. Par ...
In this paper we aim at controlling physically meaningful quantities with emphasis on environmental applications. This is carried out by an efficient numerical procedure combining the goal-oriented framework [R. Becker, R. Rannacher, An optimal control app ...
BACKGROUND: High-density oligonucleotide arrays (HDONAs) are a powerful tool for assessing differential mRNA expression levels. To establish the statistical significance of an observed change in expression, one must take into account the noise introduced b ...
The authors achieve robust estimation of parametric models through the use of weighted maximum likelihood techniques. A new estimator is proposed and its good properties illustrated through examples. Ease of implementation is an attractive property of the ...