A Jacobi-Type Eigensolver for Diagonally Dominant Symmetric Matrices
It offers a specialized method for eigenpair computation in diagonally dominant symmetric matrices, but its applicability is limited to this specific matrix class.
This paper presents a Jacobi-type iteration for computing a specified eigenpair of a symmetric matrix, achieving linear convergence for diagonally dominant matrices with quadratic cost per iteration.
This paper presents a Jacobi-type iteration for computing a given specified eigenpair of a symmetric matrix. For a certain class of diagonally dominant matrices, the procedure is shown to converge at a linear rate depending on how the matrix is significantly dominated. The cost per iteration is generally quadratic. Therefore, the proposed procedure can compute an approximation of the desired eigenpair in quadratic time.