Skip to main content

Constrained regularized least squares problems

Inverse Problems And Optimization

  • 1285 Accesses

Part of the Lecture Notes in Mathematics book series (LNM,volume 1497)

Keywords

  • Conjugate Gradient Method
  • Linear Inequality
  • Descent Direction
  • Newton Iteration
  • Lower Constraint

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   54.99
Price excludes VAT (Canada)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   69.99
Price excludes VAT (Canada)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. L-E. Andersson, T. Elfving: Interpolation and Approximation by Monotone Cubic Splines. LiTH-MAT-R-1990-03. Linköping University (1990). (To appear in J. of Approx. Theory).

    Google Scholar 

  2. Y. Censor, T. Elfving, G.T. Herman: Regularized least squares solution of linear inequalities. Technical Report MIPG97. Dept. of Radiology, University of Pennsylvania (1985).

    Google Scholar 

  3. P. Concus, G.H. Golub, D.P. O'Leary: Numerical Solution of Nonlinear Elliptic Partial Differential Equations by a Generalized Conjugate Gradient Method. Computing 19, 321–339 (1978).

    CrossRef  Google Scholar 

  4. P.E. Gill, W. Murray, M.H. Wright: Practical Optimization. Academic Press 1981.

    Google Scholar 

  5. G. T. Herman: Image Reconstruction from Projections: The fundamentals of computerized tomography. Academic Press 1980.

    Google Scholar 

  6. B.K. Lind: Properties of an algorithm for solving the inverse problem in radiation theraphy. Inverse Problems 6, 415–426 (1990).

    CrossRef  Google Scholar 

  7. C.A. Micchelli, F.I. Utreras: Smoothing and Interpolation in a convex Subset of a Hilbert Space. SIAM J. Sci. Stat. Comput. 9, 728–747 (1988).

    CrossRef  Google Scholar 

  8. F. Natterer: The Mathematics of Computerized Tomography. Teubner, Wiley 1986.

    Google Scholar 

  9. P.W. Smith, H. Wolkowicz: A nonlinear equation for linear Programming. Math. Programming 34, 235–238 (1986).

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 1991 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Elfving, T. (1991). Constrained regularized least squares problems. In: Herman, G.T., Louis, A.K., Natterer, F. (eds) Mathematical Methods in Tomography. Lecture Notes in Mathematics, vol 1497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0084516

Download citation

  • DOI: https://doi.org/10.1007/BFb0084516

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-54970-3

  • Online ISBN: 978-3-540-46615-4

  • eBook Packages: Springer Book Archive