Regularization Tools version 4.0 for Matlab 7.3
By Per Christian Hansen. Numerical Algorithms, 2007
809 citations recorded by the source corpus.
Subfields: Atomic and Molecular Physics, and Optics, Mathematical Physics, Mechanics of Materials
View Paper: https://www.semanticscholar.org/paper/1769de11213513e165ea49c15e4596ef5e7c0144
How researchers see this paper
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In Atomic and Molecular Physics, and Optics
- Jakub Konecný
- Lothar Reichel
- Michiel E. Hochstenbach
- Daniel J. Gerth
- Esther Klann
- Ronny Ramlau
- Maria Saxild-Hansen
In Mathematical Physics
- Jakub Konecný
- Lothar Reichel
- Michiel E. Hochstenbach
- Daniel J. Gerth
- Esther Klann
- Ronny Ramlau
- Maria Saxild-Hansen
In Mechanics of Materials
- Jakub Konecný
- Lothar Reichel
- Michiel E. Hochstenbach
- Daniel J. Gerth
- Esther Klann
- Ronny Ramlau
- Maria Saxild-Hansen
Citations in the corpus
- Stochastic, Distributed and Federated Optimization for Machine Learning (2017, methodology): “In this section we utilize the Regularization Toolbox [72].12 We use the blur function available therein to obtain the original image and generate a blurred image (we choose following values of parameters for blur function: N = 256, band=9, sigma=10).”
- Fractional Tikhonov regularization for linear discrete ill-posed problems (2011, methodology): “We show numerical experiments carried out for ten linear discrete ill-posed problems from Regularization Tools [6].”
- On fractional Tikhonov regularization (2015, positive): “1) provided in Regularization Tools [3].”
- AIR Tools - A MATLAB package of algebraic iterative reconstruction methods (2012, background): “1 shows the first nine left singular vectors ui for the test problem shaw from Regularization Tools [21] with white noise level δ = 10−3.”