Ill-posed problems Ax = h are discussed in which A is Hermitian,and postive definite; a bound ║Bx║ ≤ β is prescribed. A minimum principle is given for an approximate solution x^. Comparisons are made with the least-squares solutions of K. Miller, A. Tikhonov, et al. Applications are made to deconvolution, the backward heat equation, and the inversion of ill-conditioned matrices. If A and B are positive-definite, commuting matrices, the approximation x^ is shown to be about as accurate as the least-squares solution and to be more quickly and accurately computable
Abstract. The condition number of a problem measures the sensitivity of the answer to small changes ...
In this paper we develop a procedure to deal with a family of parameter-dependent ill-posed problems...
In the paper there are discussed certain issues concerning ill-posed problems that fre-quently appea...
AbstractA problem is said to be ill-posed if the solution of the problem does not depend continuousl...
Problems that appear in practical situations are usually categorized into two, namely, the direct pr...
AbstractStraightforward solution of discrete ill-posed least-squares problems with error-contaminate...
AbstractIn this paper we derive conditions under which the constrained Tikhonov-regularized solution...
Many problems in science and engineering give rise to linear systems of equations that are commonly ...
Many applications in science and engineering require the solution of large linear discrete ill-posed...
Straightforward solution of discrete ill-posed least-squares problems with error-contaminated data d...
In this paper we deal with the `strength' of ill-posedness for ill-posed linear operator equations A...
In the present paper for a stable solution of severely ill-posed problems with perturbed input data,...
Choosing the regularization parameter for an ill-posed problem is an art based on good heuristics an...
Discretizations of inverse problems lead to systems of linear equations with a highly ill-condition...
AbstractA new regularized projection method was developed for numerically solving ill-posed equation...
Abstract. The condition number of a problem measures the sensitivity of the answer to small changes ...
In this paper we develop a procedure to deal with a family of parameter-dependent ill-posed problems...
In the paper there are discussed certain issues concerning ill-posed problems that fre-quently appea...
AbstractA problem is said to be ill-posed if the solution of the problem does not depend continuousl...
Problems that appear in practical situations are usually categorized into two, namely, the direct pr...
AbstractStraightforward solution of discrete ill-posed least-squares problems with error-contaminate...
AbstractIn this paper we derive conditions under which the constrained Tikhonov-regularized solution...
Many problems in science and engineering give rise to linear systems of equations that are commonly ...
Many applications in science and engineering require the solution of large linear discrete ill-posed...
Straightforward solution of discrete ill-posed least-squares problems with error-contaminated data d...
In this paper we deal with the `strength' of ill-posedness for ill-posed linear operator equations A...
In the present paper for a stable solution of severely ill-posed problems with perturbed input data,...
Choosing the regularization parameter for an ill-posed problem is an art based on good heuristics an...
Discretizations of inverse problems lead to systems of linear equations with a highly ill-condition...
AbstractA new regularized projection method was developed for numerically solving ill-posed equation...
Abstract. The condition number of a problem measures the sensitivity of the answer to small changes ...
In this paper we develop a procedure to deal with a family of parameter-dependent ill-posed problems...
In the paper there are discussed certain issues concerning ill-posed problems that fre-quently appea...