How Far Should You Go With the Lanczos Process.
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)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 18, 1978
- Accession Number
- ADA059145
Entities
People
- Beresford N. Parlett
- W. Kahan
Organizations
- University of California, Berkeley