An estimate of a state vector for a physical system when the weight matrix in the method of least squares is a function of this vector is considered. An iterative procedure is proposed for calculating the desired estimate. Conditions for the existence and uniqueness of the limit of this procedure are obtained, and a domain is found which contains the limit estimate. A second method for calculating the desired estimate which reduces to the solution of a system of algebraic equations is proposed. The question of applying Newton's method of tangents to solving the given system of algebraic equations is considered and conditions for the convergence of the modified Newton's method are obtained. Certain properties of the estimate obtained are pre...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
AbstractThis paper presents a method for positive definite constrained least-squares estimation of m...
Several models in data analysis are estimated by minimizing the objective function defined as the re...
The first part of this paper gives a general approach to the least squares estimation of the weighti...
In most problems in mathematics, science, engineering, and economics it is sufficient to find an equ...
The best least squares fitL A to a matrixA in a spaceL can be useful to improve the rate of converge...
We review the development and extensions of the classical total least squares method and describe al...
We review the development and extensions of the classical total least squares method and describe al...
In this paper, least-squares method with matrix decomposition is revisited and a multiple model form...
Abstract. Modeling the mean of a random variable as a function of unknown parameters leads to a nonl...
In order to improve calculation efficiency of parameter estimation, an algorithm for multivariate we...
AbstractAn iterative least squares parameter estimation algorithm is developed for controlled moving...
This thesis presents a class of methods for solving nonlinear least squares problems. A comprehensiv...
In contrast to general optimization problems or optimal control problems it is not sufficient to cal...
In this paper, we address the accuracy of the results for the overdetermined full rank linear least ...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
AbstractThis paper presents a method for positive definite constrained least-squares estimation of m...
Several models in data analysis are estimated by minimizing the objective function defined as the re...
The first part of this paper gives a general approach to the least squares estimation of the weighti...
In most problems in mathematics, science, engineering, and economics it is sufficient to find an equ...
The best least squares fitL A to a matrixA in a spaceL can be useful to improve the rate of converge...
We review the development and extensions of the classical total least squares method and describe al...
We review the development and extensions of the classical total least squares method and describe al...
In this paper, least-squares method with matrix decomposition is revisited and a multiple model form...
Abstract. Modeling the mean of a random variable as a function of unknown parameters leads to a nonl...
In order to improve calculation efficiency of parameter estimation, an algorithm for multivariate we...
AbstractAn iterative least squares parameter estimation algorithm is developed for controlled moving...
This thesis presents a class of methods for solving nonlinear least squares problems. A comprehensiv...
In contrast to general optimization problems or optimal control problems it is not sufficient to cal...
In this paper, we address the accuracy of the results for the overdetermined full rank linear least ...
In computational science it is common to describe dynamic systems by mathematical models in forms of...
AbstractThis paper presents a method for positive definite constrained least-squares estimation of m...
Several models in data analysis are estimated by minimizing the objective function defined as the re...