Add to ORKGEstimation of unknowns in the presence of noise and uncertainty is an active area of study, because no method handles all cases well, or even satisfactorily. The basic problem considered is the linear system, b, where A and b are given matrices with noise and uncertainty from measurements or modeling
. We pose and solve a parameter estimation problem in the presence of bounded data uncertainties. Th...
In this paper, estimation and identification theories will be examined with the goal of determining ...
Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the ...
Estimation of unknowns in the presence of noise and uncertainty is an active area of study, because ...
We computationally investigate two approaches for uncertainty quantification in inverse problems for...
The parameter estimation problem of linear systems from input output measurements, corrupted with no...
The least mean-squared error linear estimation problem of signals in systems with uncertain observat...
Nahi [2] considered the optimal linear estimation with uncertain observations. In his model, the bin...
AbstractThis paper deals with approximating linear operators from information contaminated with boun...
This paper deals with some issues involving a parameter estimation approach that yields estimates co...
In the field of water technology, forward uncertainty propagation is frequently used, whereas backwa...
In this paper we present a class of bounded-uncertainty estimators as the solution of a classic esti...
We formulate and solve a new parameter estimation problem in the presence of bounded model uncertain...
A simple method for determination of the estimation error of physical parameters due to noise and un...
The problem of minimax estimation in the linear regression model is considered under the assumption ...
. We pose and solve a parameter estimation problem in the presence of bounded data uncertainties. Th...
In this paper, estimation and identification theories will be examined with the goal of determining ...
Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the ...
Estimation of unknowns in the presence of noise and uncertainty is an active area of study, because ...
We computationally investigate two approaches for uncertainty quantification in inverse problems for...
The parameter estimation problem of linear systems from input output measurements, corrupted with no...
The least mean-squared error linear estimation problem of signals in systems with uncertain observat...
Nahi [2] considered the optimal linear estimation with uncertain observations. In his model, the bin...
AbstractThis paper deals with approximating linear operators from information contaminated with boun...
This paper deals with some issues involving a parameter estimation approach that yields estimates co...
In the field of water technology, forward uncertainty propagation is frequently used, whereas backwa...
In this paper we present a class of bounded-uncertainty estimators as the solution of a classic esti...
We formulate and solve a new parameter estimation problem in the presence of bounded model uncertain...
A simple method for determination of the estimation error of physical parameters due to noise and un...
The problem of minimax estimation in the linear regression model is considered under the assumption ...
. We pose and solve a parameter estimation problem in the presence of bounded data uncertainties. Th...
In this paper, estimation and identification theories will be examined with the goal of determining ...
Modeling and Inverse Problems in the Presence of Uncertainty collects recent research-including the ...