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.

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1975
Accession Number
ADA016294

Entities

People

  • B. Parlett
  • W. Kahan

Organizations

  • University of California, Berkeley

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Computational Complexity
  • Computations
  • Eigenvalues
  • Mathematical Analysis
  • Mathematics
  • Sparse Matrix

Fields of Study

  • Mathematics

Readers

  • Distributed Systems and Data Platform Development
  • Linear Algebra