Results 131 to 140 of about 77,719 (148)

Modular solvers for image restoration problems using the discrepancy principle

Numerical Linear Algebra with Applications, 2002
AbstractMany problems in image restoration can be formulated as either an unconstrained non‐linear minimization problem, usually with aTikhonov‐like regularization, where the regularization parameter has to be determined; or as a fully constrained problem, where an estimate of the noise level, either the variance or the signal‐to‐noise ratio, is ...
Peter Blomgren, Tony F. Chan
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What do we Learn from the Discrepancy Principle?

Zeitschrift für Analysis und ihre Anwendungen, 2006
The author analyzes the discrepancy principle when smoothness is given in terms of general source conditions. As it turns out, this framework is particularly well suited to reveal the mechanism under which this principle works. For general source conditions there is no explicit way to compute rates of convergence.
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Optimization aspects of the generalized discrepancy principle in regularization

Optimization, 1986
The generalized discrepancy principle in regularization is investigated from the optimization point of view. Tikhonov's regularization method can be considered as a Lagrange multiplier method. This approach allows formulating a search algorithm for choosing the regularization parameter.
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Morozov's discrepancy principle and Tikhonov-type functionals

Inverse Problems, 2008
This paper deals with the well-known discrepancy principle of Morozov. We show that the principle can be used as an a posteriori choice rule for determining the regularization parameter of Tikhonov regularization considering more general penalty terms than the classical quadratic one. We show regularization properties as well as convergence rates.
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On the connection between the generalized discrepancy method and the generalized discrepancy principle for non-linear ill-posed problems

USSR Computational Mathematics and Mathematical Physics, 1982
The generalized residual principle is a method for choosing the regularization parameter in Tikhonov's method for the solution of ill- posed problems. It is shown that the approximations computed by this choice converge to the so-called normal solution of the problem.
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The Attitudes Towards and Enactment of Psychosocial Rehabilitation Principles: Discrepancies and Correlates

International Journal of Social Psychiatry, 2007
Background: Previous literature suggests that attitudes have critical effects on recovery outcomes. Yet mental health professionals' attitudes towards psychiatric rehabilitation principles (PRP) have not been fully addressed. Whether the professionals could act in accordance with attitudes has also not been examined.
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A generalized discrepancy principle

USSR Computational Mathematics and Mathematical Physics, 1973
Goncharskij, A. V., Leonov, A. S., Yagola, A. G.   +2 more
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Numerical realization of an optimal discrepancy principle for Tikhonov-regularization in Hilbert scales

Computing, 1987
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Stochastic projection spline regularization based on the discrepancy principle

USSR Computational Mathematics and Mathematical Physics, 1987
See the review in Zbl 0636.65086.
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MOROZOV'S DISCREPANCY PRINCIPLE FOR TIKHONOV-REGULARIZATION OF NONLINEAR OPERATORS

Numerical Functional Analysis and Optimization, 2002
ABSTRACT We consider Morozov's discrepancy principle for Tikhonov-regularization of nonlinear operator equations. It is shown that minor restrictions to the operator F and the solution x* of the equation already guarantee the existence of a regularization parameter α such that holds, and a convergence rate result is given.
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