A block variational procedure for the iterative diagonalization of non-Hermitian random-phase approximation matrices.

An iterative method for the Hermitian-generalized Hamiltonian solutions to the inverse problem AX=B with a submatrix constraint

In this paper, an iterative method is proposed for solving the matrix inverse problem $AX=B$ for Hermitian-generalized Hamiltonian matrices with a submatrix constraint. By this iterative method, for any initial matrix $A_0$, a solution $A^*$ can be obtained in finite iteration steps in the absence of roundoff errors, and the solution with least norm can be obtained by choosing a special kind of...

Computing the Matrix Geometric Mean of Two HPD Matrices: A Stable Iterative Method

A new iteration scheme for computing the sign of a matrix which has no pure imaginary eigenvalues is presented. Then, by applying a well-known identity in matrix functions theory, an algorithm for computing the geometric mean of two Hermitian positive definite matrices is constructed. Moreover, another efficient algorithm for this purpose is derived free from the computation of principal matrix...

Sparse Generalized Fourier Transforms ∗

Block-diagonalization of sparse equivariant discretization matrices is studied. Such matrices typically arise when partial differential equations that evolve in symmetric geometries are discretized via the finite element method or via finite differences. By considering sparse equivariant matrices as equivariant graphs, we identify a condition for when block-diagonalization via a sparse variant ...

Iterative algorithms for families of variational inequalities fixed points and equilibrium problems

Joint Approximate Diagonalization of Positive Deenite Hermitian Matrices

This paper provides an iterative algorithm to jointly approximately di-agonalize K Hermitian positive deenite matrices ? 1 , : : : , ? K. Speciically it calculates the matrix B which minimizes the criterion P K k=1 n k log det diag(BC k B) ? log det(BC k B)], n k being positive numbers, which is a measure of the deviation from diagonality of the matrices BC k B. The convergence of the algorithm...