IDR explained.
Image restoration through subimages and confidence images.
Implementation of the gmr algorithm for large symmetric eigenproblems
Implementing parallel elliptic solver on a Beowulf cluster.
Improved convergence bounds for smoothed aggregation method: linear dependence of the convergence rate on the number of levels
The smoothed aggregation method has became a widely used tool for solving the linear systems arising by the discretization of elliptic partial differential equations and their singular perturbations. The smoothed aggregation method is an algebraic multigrid technique where the prolongators are constructed in two steps. First, the tentative prolongator is constructed by the aggregation (or, the generalized aggregation) method. Then, the range of the tentative prolongator is smoothed by a sparse linear...
Improved convergence estimate for a multiply polynomially smoothed two-level method with an aggressive coarsening
A variational two-level method in the class of methods with an aggressive coarsening and a massive polynomial smoothing is proposed. The method is a modification of the method of Section 5 of Tezaur, Vaněk (2018). Compared to that method, a significantly sharper estimate is proved while requiring only slightly more computational work.
Improved initialization of the accelerated and robust QR-like polynomial root-finding.
Improving backward stability of Sakurai-Sugiura method with balancing technique in polynomial eigenvalue problem
One of the most efficient methods for solving the polynomial eigenvalue problem (PEP) is the Sakurai-Sugiura method with Rayleigh-Ritz projection (SS-RR), which finds the eigenvalues contained in a certain domain using the contour integral. The SS-RR method converts the original PEP to a small projected PEP using the Rayleigh-Ritz projection. However, the SS-RR method suffers from backward instability when the norms of the coefficient matrices of the projected PEP vary widely. To improve the backward...
Inclusion Theorems for a Section of a Matrix.
Incremental unknowns for solving partial differential equations.
Incremental unknowns method and compact schemes
Incremental unknowns on nonuniform meshes
Index Transforms for Multidimensional DFT's and Convolutions.
Index Transforms for N-dimensional DFT's.
Inequality-based approximation of matrix eigenvectors
A novel procedure is given here for constructing non-negative functions with zero-valued global minima coinciding with eigenvectors of a general real matrix A. Some of these functions are distinct because all their local minima are also global, offering a new way of determining eigenpairs by local optimization. Apart from describing the framework of the method, the error bounds given separately for the approximation of eigenvectors and eigenvalues provide a deeper insight into the fundamentally...
Inertias and ranks of some Hermitian matrix functions with applications
Let S be a given set consisting of some Hermitian matrices with the same size. We say that a matrix A ∈ S is maximal if A − W is positive semidefinite for every matrix W ∈ S. In this paper, we consider the maximal and minimal inertias and ranks of the Hermitian matrix function f(X,Y) = P − QXQ* − TYT*, where * means the conjugate and transpose of a matrix, P = P*, Q, T are known matrices and for X and Y Hermitian solutions to the consistent matrix equations AX =B and YC = D respectively. As applications,...
Inexact Newton preconditioning techniques for large symmetric eigenvalue problems.
Infinite products and paracontracting matrices.
Influence of preconditioning and blocking on accuracy in solving Markovian models
The article considers the effectiveness of various methods used to solve systems of linear equations (which emerge while modeling computer networks and systems with Markov chains) and the practical influence of the methods applied on accuracy. The paper considers some hybrids of both direct and iterative methods. Two varieties of the Gauss elimination will be considered as an example of direct methods: the LU factorization method and the WZ factorization method. The Gauss-Seidel iterative method...
Inhomogenous RefinementEquations.