Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
  1. Home
  2. Search

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

1 results

  • 6 - Computational Linear Algebra

  • from Part II - Numerical Methods
  • Kevin W. Cassel, Illinois Institute of Technology
  • Book:
    Matrix, Numerical, and Optimization Methods in Science and Engineering
    Published online:
    18 February 2021
    Print publication:
    04 March 2021, pp 315-375

  • Summary

    Computational linear algebra builds on the methods in Part I for solving systems of linear algebraic equations and the algebraic eigenproblem appropriate for small systems to methods amenable to approximate computer solutions for large systems.These include direct and iterative methods for solving systems of equations, such as LU decomposition and Gauss-Seidel iteration.A popular algorithm based on QR decomposition is described for solving large algebraic eigenproblems for the full spectrum of eigenpairs, and the Arnoldi method for a subset of eigenpairs of sparse matrices.