
AbstractBathe's basic algorithm of subspace iteration for the solution of the symmetric eigenvalue problem is improved by including a Chebyshev filtering mechanism. To obtain satisfactory convergence for the largest eigenvalues, a shifting strategy is adopted. The shift factor is approximately computed by the Lanczos process.
Numerical computation of eigenvalues and eigenvectors of matrices, Chebyshev filtering, subspace iteration, Lanczos process, symmetric eigenvalue problem, shifting strategy, largest eigenvalues
Numerical computation of eigenvalues and eigenvectors of matrices, Chebyshev filtering, subspace iteration, Lanczos process, symmetric eigenvalue problem, shifting strategy, largest eigenvalues
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