A refined Jacobi-Davidson method is proposed to overcome the possible nonconvergence of Ritz vectors by computing certain refined approximation eigenvect.

Parallel block Jacobi-Davidson method for solving large generalized eigenvalue problems and it s application;

The system state matrix s critical eigenvalues with increasing damping ratios are obtained by Jacobi-Davidson method, which catches the essence of power system electromechanical oscillation analysis, avoids the calculation of a lot of redundant eigenvalues and reduces the calculation amount evidently.

The Jacobi-Davidson method is used to calculate the critical eigenvalues of the system state matrix.

A parallel block Davidson method is presented for solving extreme eigenpairs of large sparse symmetric matrix based on PC network parallel environment and shared memory parallel environment.

In this paper ,Davidson Method, a method of computing the eigenvalues of large?sparse and symmetric matrix is introduced .

Davidson method together with its variants is considered as the most popular solution approaches to large scale eigenvalue problems.

Refining-strategy of block Davidson method for solving large sparse eigenproblems;

However,the corresponding Ritz vectors obtained by block Davidson method always converge more slowly than the Ritz values.

This paper mainly studies the restarting process of the Davidson method,and proposes two new methods : refined block Davidson method and refined block Davidson method with deflation.

A parallel block Davidson method is presented for solving extreme eigenpairs of large sparse symmetric matrix based on PC network parallel environment and shared memory parallel environment.