A general heuristic for choosing the regularization parameter in ill-posed problems

Real time proximity effects neurocorrector

Microelectronic Engineering

L- and Θ-curve approaches for the selection of regularization parameter in geophysical diffraction tomography

Computers & Geosciences

Choice of the regularization parameter in ill-posed problems with rough estimate of the noise level of data

MATH'05 Proceedings of the 7th WSEAS International Conference on Applied Mathematics

Comparing different types of approximators for choosing the parameters in the regularization of ill-posed problems

Computers & Mathematics with Applications

Heuristic Parameter-Choice Rules for Convex Variational Regularization Based on Error Estimates

SIAM Journal on Numerical Analysis

Comparison of parameter choices in regularization algorithms in case of different information about noise level

Calcolo: a quarterly on numerical analysis and theory of computation

Original Article: Comparingparameter choice methods for regularization of ill-posed problems

Mathematics and Computers in Simulation

Multi-parameter Tikhonov regularization and model function approach to the damped Morozov principle for choosing regularization parameters

Journal of Computational and Applied Mathematics