Add to ORKGAbstract. We consider a general projection method for approximating the minimal norm least squares solution of a linear operator equation of the first kind. A necessary and sufficient condition for weak convergence of the finite dimensional approximations is given and a convergence rate in the norm topology is provided for the case of a compact operator. 1. Introduction. W
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
—A minimum-length vector is found for a simplex in a finite-dimensional Euclidean space. The algorit...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
AbstractA convergence theorem for J. W. Lee and P. M. Prenter's filtered least squares method for so...
AbstractLet T be a bounded linear operator from one Hilbert space to another. A class of gradient me...
AbstractWe provide sufficient conditions for the convergence of a certain Newton-like method to the ...
AbstractThis article investigates the projection-difference method for a Cauchy problem for a linear...
AbstractBased on the projection theorem in Hilbert space, by making use of the generalized singular ...
2siIn this paper we analyze the behavior of the LSQR algorithm for the solution of compact operator...
Abstract. In [4] the authors proposed a collocation algorithm for approximating the minimal norm lea...
In this paper we prove both the L1-norm and the BV-norm convergence for a piecewise linear least squ...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
Abstract. This paper deals with the problem of finding the minimum norm least-squares solution of a ...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
Many recent problems in signal processing and machine learning such as compressed sensing, image res...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
—A minimum-length vector is found for a simplex in a finite-dimensional Euclidean space. The algorit...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
AbstractA convergence theorem for J. W. Lee and P. M. Prenter's filtered least squares method for so...
AbstractLet T be a bounded linear operator from one Hilbert space to another. A class of gradient me...
AbstractWe provide sufficient conditions for the convergence of a certain Newton-like method to the ...
AbstractThis article investigates the projection-difference method for a Cauchy problem for a linear...
AbstractBased on the projection theorem in Hilbert space, by making use of the generalized singular ...
2siIn this paper we analyze the behavior of the LSQR algorithm for the solution of compact operator...
Abstract. In [4] the authors proposed a collocation algorithm for approximating the minimal norm lea...
In this paper we prove both the L1-norm and the BV-norm convergence for a piecewise linear least squ...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
Abstract. This paper deals with the problem of finding the minimum norm least-squares solution of a ...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
Many recent problems in signal processing and machine learning such as compressed sensing, image res...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
—A minimum-length vector is found for a simplex in a finite-dimensional Euclidean space. The algorit...
Sufficient conditions are found for the asymptotic optimality of projection methods as applied to li...
