Accession Number:

ADA059145

Title:

How Far Should You Go With the Lanczos Process.

Descriptive Note:

Final memorandum rept.,

Corporate Author:

CALIFORNIA UNIV BERKELEY ELECTRONICS RESEARCH LAB

Personal Author(s):

Report Date:

1978-07-18

Pagination or Media Count:

18.0

Abstract:

The Lanczos algorithm can be used to approximate both the largest and smallest eigenvalues of a symmetric matrix whose order is so large that similarity transformations are not feasible. The algorithm builds up a tridiagonal matrix row by row and the key question is when to stop. An analysis leads to a stopping criterion which is inspired by a useful error bound on the computed eigenvalues. Author

Subject Categories:

  • Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE