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

  • 10 - Least-Squares Methods

  • from Part III - Least Squares and Optimization
  • 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 529-559

  • Summary

    Least-squares methods provide the mathematical foundation for optimization of algebraic systems.They can be applied to overdetermined systems, having more equations than unknowns, or undertermined systems, having fewer equations than unknowns.The optimization may involve constraints or be subject to a penalty function.Numerical methods, namely the conjugate-gradient and GMRES methods, that are based on least-squares optimization method are discussed in detail and put into the context of other Krylov-based methods.