David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
A heuristic argument and supporting numerical results are given to demonstrate that a block Lanczos procedure can be used to compute simultaneously a few of the algebraically largest and smallest eigenvalues and a corresponding eigenspace of a large, sparse, symmetric matrix A. This block procedure can be used, for example, to compute appropriate parameters for iterative schemes used in solving the equation Ax=b. Moreover, if there exists an efficient method for repeatedly solving the equation (A-σI)X=B, this procedure can be used to determine the interior eigenvalues (and corresponding eigenvectors) of A closest to σ. © 1978 BIT Foundations.
David W. Jacobs, Daphna Weinshall, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence
Timothy J. Wiltshire, Joseph P. Kirk, et al.
SPIE Advanced Lithography 1998
Tong Zhang, G.H. Golub, et al.
Linear Algebra and Its Applications
L Auslander, E Feig, et al.
Advances in Applied Mathematics