Abstract
The variational form of mollification fits in an extension of the generalized Tikhonov regularization. Using tools from variational analysis, we prove asymptotic consistency results for both this extended framework and the particular form of mollification that one obtains when building on the notion of target object.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Alibaud, N., Maréchal, P., Saesor, Y.: A variational approach to the inversion of truncated Fourier operators. Inverse Probl. 25(4), 045002 (2009)
Bonnefond, X., Maréchal, P.: A variational approach to the inversion of some compact operators. Pac. J. Optim. 5(1), 97–110 (2009)
Engl, H.W., Hanke, M., Neubauer, A.: Regularization of Inverse Problems, vol. 375. Springer Science & Business Media (1996)
Friedrichs, K.O.: The identity of weak and strong extensions of differential operators. Trans. Am. Math. Soc. 55(1), 132–151 (1944)
Hào, D.N.: A mollification method for ill-posed problems. Numer. Math. 68, 469–506 (1994)
Hohage, T., Maréchal, P., Vanhems, A.: A mollifier approach to the deconvolution of probability densities. Part 2: Convergence rates (2020). Submitted
Lannes, A., Roques, S., Casanove, M.J.: Stabilized reconstruction in signal and image processing: I. partial deconvolution and spectral extrapolation with limited field. J. Mod. Opt. 34(2), 161–226 (1987)
Louis, A.K., Maass, P.: A mollifier method for linear operator equations of the first kind. Inverse Probl. 6(3), 427 (1990)
Maréchal, P., Simar, L., Vanhems, A.: A mollifier approach to the deconvolution of probability densities. Part 1: The methodology and its comparison to classical methods (2020). Submitted
Maréchal, P., Simo Tao Lee, W.C., Vanhems, A.: A mollifier approach to the nonparametric instrumental regression problem (2020). Submitted
Maréchal, P., Togane, D., Celler, A.: A new reconstruction methodology for computerized tomography: FRECT (fourier regularized computed tomography). IEEE Trans. Nucl. Sci. 47(4), 1595–1601 (2000)
Murio, D.A.: The Mollification Method and the Numerical Solution of Ill-Posed Problems. Wiley (2011)
Natterer, F.: The Mathematics of Computerized Tomography. SIAM (2001)
Schuster, T.: The Method of Approximate Inverse: Theory and Applications, vol. 1906. Springer (2007)
Tikhonov, A.N., Arsenin, V.Y.: Methods for Solving Ill-Posed Problems. Wiley (1977)
Wikipedia contributors: Mollifier—Wikipedia, the free encyclopedia. https://en.wikipedia.org/w/index.php?title=Mollifier&oldid=950509587 (2020). Accessed 17 April 2020
Acknowledgements
The author wishes to thank Nathaël Alibaud for fruitful discussions on the subject, which led to significant improvements of this paper.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Maréchal, P. (2021). A Note on Quadratic Penalties for Linear Ill-Posed Problems: From Tikhonov Regularization to Mollification. In: Laha, V., Maréchal, P., Mishra, S.K. (eds) Optimization, Variational Analysis and Applications. IFSOVAA 2020. Springer Proceedings in Mathematics & Statistics, vol 355. Springer, Singapore. https://doi.org/10.1007/978-981-16-1819-2_9
Download citation
DOI: https://doi.org/10.1007/978-981-16-1819-2_9
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-16-1818-5
Online ISBN: 978-981-16-1819-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)