Results 71 to 80 of about 180,343 (197)
An interior-point method for large constrained discrete ill-posed problems
Journal of Computational and Applied Mathematics, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
MORIGI, SERENA +2 more
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, 2013 This paper discusses the solution of nonlinear integral equations with noisy integral kernels as they appear in nonparametric instrumental regression. We propose a regularized Newton-type iteration and establish convergence and convergence rate results ...
Dunker, Fabian +4 more
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An efficient discretization scheme for solving ill-posed problems
Journal of Mathematical Analysis and Applications, 2006 For the stable numerical solution of linear ill-posed operator equations \(Ax=y\) with some bounded linear forward operator \(A: X \to X\) mapping in the Hilbert space \(X\) a finite-dimensional approximation scheme of Tikhonov's regularization method with some new aspects is dicussed.
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Nonparametric Estimation in Random Coefficients Binary Choice Models [PDF]
This paper considers random coefficients binary choice models. The main goal is to estimate the density of the random coefficients nonparametrically. This is an ill-posed inverse problem characterized by an integral transform. A new density estimator for
Eric Gautier, Yuichi Kitamura
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Stabilised finite element methods for ill-posed problems with conditional stability
, 2015 In this paper we discuss the adjoint stabilised finite element method introduced in, E. Burman, Stabilized finite element methods for nonsymmetric, noncoercive and ill-posed problems.
Burman, Erik
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Inverse Heat Conduction Methods in the CHAR Code for Aerothermal Flight Data Reconstruction [PDF]
Reconstruction of flight aerothermal environments often requires the solution of an inverse heat transfer problem, which is an ill-posed problem of determining boundary conditions from discrete measurements in the interior of the domain.
Amar, Adam J., Oliver, A. Brandon
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Regularization parameter determination for discrete ill-posed problems
, 2014 Straightforward solution of discrete ill-posed linear systems of equations or least-squares problems with error contaminated data does not, in general, give meaningful results, because the propagated error destroys the computed solution. The problems have to be modified to reduce their sensitivity to the error in the data. The amount of modification is
Hochstenbach, M.E. +2 more
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Fractional regularization matrices for linear discrete ill-posed problems
, 2013 The numerical solution of linear discrete ill-posed problems typically requires regularization. Two of the most popular regularization methods are due to Tikhonov and Lavrentiev. These methods require the choice of a regularization matrix. Common choices include the identity matrix and finite difference approximations of a derivative operator.
Hochstenbach, M.E. +2 more
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Tikhonov regularization and the L-curve for large discrete ill-posed problems
, 2000 D. Calvetti +3 more
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Lagrangian methods for the regularization of discrete ill-posed problems
, 2005 In many science and engineering applications, the discretization of linear ill-posed problems gives rise to large ill-conditioned linear systems with right-hand side degraded by noise. The solution of such linear systems requires the solution of a minimization problem with one quadratic constraint depending on an estimate of the variance of the noise.
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