Iterative Solution Methods

By Martin Burger, Barbara Kaltenbacher, Andreas Neubauer. Handbook of Mathematical Methods in Imaging, 2015

559 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

B‐preconditioned minimization algorithms for variational data assimilation with the dual formulation (2014, background): “Alternatively, B-preconditioning of the linear system (5) can be achieved by employing B as a right symmetric preconditioner (Nour-Omid et al., 1988; Axelsson, 1996; Chan et al., 1999).”
CatMAP: A Software Package for Descriptor-Based Microkinetic Mapping of Catalytic Trends (2015, methodology): “One solution to the problem is to use a constrained minimization algorithm [50].”
Compressive Sensing in Electromagnetics - A Review (2015, methodology): “, half-quadratic regularization [105], conjugate gradient [106], or convex programming [38] methods) when applied to ‘1-based functionals [101–103].”
Fusing Hyperspectral and Multispectral Images via Coupled Sparse Tensor Factorization (2018, background): “In fact, the convergence of CG is linear and depends on the ratio between the largest and the smallest eigenvalues of the system matrix associated with (19) [49].”
Regularized HSS iteration methods for saddle-point linear systems (2017, methodology): “2 we present the algorithmic description of the RHSS iteration method.”