Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content

On nondecreasing sequences of regularization parameters for nonstationary iterated Tikhonov

  • Original   Paper
  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

Nonstationary iterated Tikhonov is an iterative regularization method that requires a strategy for defining the Tikhonov regularization parameter at each iteration and an early termination of the iterative process. A classical choice for the regularization parameters is a decreasing geometric sequence which leads to a linear convergence rate. The early iterations compute quickly a good approximation of the true solution, but the main drawback of this choice is a rapid growth of the error for later iterations. This implies that a stopping criteria, e.g. the discrepancy principle, could fail in computing a good approximation. In this paper we show by a filter factor analysis that a nondecreasing sequence of regularization parameters can provide a rapid and stable convergence. Hence, a reliable stopping criteria is no longer necessary. A geometric nondecreasing sequence of the Tikhonov regularization parameters into a fixed interval is proposed and numerically validated for deblurring problems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Björck, A.: A bidiagonalization algorithm for solving large and sparse ill-posed systems of linear equations. BIT 28, 659–670 (1988)

    Article  MathSciNet  MATH  Google Scholar 

  2. Brianzi, P., Di Benedetto, F., Estatico, C.: Improvement of space-invariant image deblurring by preconditioned Landweber iterations. SIAM J. Sci. Comput. 30(3), 1430–1458 (2008)

    Article  MathSciNet  MATH  Google Scholar 

  3. Brill, M., Schock, E.: Iterative solution of ill-posed problems—a survey. Theory Pract. Appl. Geophys. 1, 13–37 (1987)

    MathSciNet  Google Scholar 

  4. Cai, J.F., Osher, S., Shen, Z.: Linearized Bregman iterations for frame-based image deblurring. SIAM J. Imag. Sci. 2(1), 226–252 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  5. Chung, J., Nagy, J.G., O’Leary, D.P.: A weighted-GCV method for Lanczos-hybrid regularization. Electron. Trans. Numer. Anal. 28, 149–167 (2007/2008)

    MathSciNet  Google Scholar 

  6. Engl, H.W., Hanke, M., Neubauer, A.: Regularization of Inverse Problems. Kluwer Academic, Dordrecht (1996)

    Book  MATH  Google Scholar 

  7. Groetsch, C.W.: The Theory of Tikhonov Regularization for Fredholm Equations of the First Kind. Pitman (Advanced Publishing Program), Boston (1984)

    MATH  Google Scholar 

  8. Hanke, M., Groetsh, C.W.: Nonstationaty iterated Tikhonov regularization. J. Optim. Theory Appl. 98(1), 37–53 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  9. Hanke, M., Hansen, P.C.: Regularization methods for large-scale problems. Surv. Math. Ind. 3, 253–315 (1993)

    MathSciNet  MATH  Google Scholar 

  10. Hanke, M., Nagy, J., Plemmons, R.: Preconditioned iterative regularization for ill-posed problems. In: Numerical Linear Algebra, pp. 141–163. de Gruyter, Berlin (1993)

    Chapter  Google Scholar 

  11. Hansen, P.C.: Regularization tools version 4.0 for MATLAB 7.3. Numer. Algorithms 46, 189–194 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  12. Hansen, P.C.: Rank-Deficient and Discrete Ill-Posed Problems. SIAM, Philadelphia (1998)

    Book  Google Scholar 

  13. Hansen, P.C., Nagy, J., O’Leary, D.P.: Deblurring Images Matrices, Spectra and Filtering. SIAM, Philadelphia (2005)

    Google Scholar 

  14. Nagy, J., Palmer, K., Perrone, L.: Iterative methods for image deblurring: a Matlab object-oriented approach. Numer. Algorithms 36, 73–93 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  15. Piana, M., Bertero, M.: Projected Landweber method and preconditioning. Inverse Probl. 13, 441–464 (1997)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Marco Donatelli.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Donatelli, M. On nondecreasing sequences of regularization parameters for nonstationary iterated Tikhonov. Numer Algor 60, 651–668 (2012). https://doi.org/10.1007/s11075-012-9593-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11075-012-9593-7

Keywords

Mathematics Subject Classifications (2010)