Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

An Alternative to Tikhonov Regularization for Linear Sampling Methods

An Alternative to Tikhonov Regularization for Linear Sampling Methods The problem of determining the shape of an obstacle from far-field measurements is considered. It is well known that linear sampling methods have been widely used for shape reconstructions obtained via the singular system of an ill conditioned discretized far-field operator. For our reconstructions we assume that the far-field data are noisy and we employ a novel regularization method that does not require determination of a regularization parameter. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Acta Applicandae Mathematicae Springer Journals

An Alternative to Tikhonov Regularization for Linear Sampling Methods

Acta Applicandae Mathematicae , Volume 112 (2) – Dec 31, 2009

Loading next page...
 
/lp/springer-journals/an-alternative-to-tikhonov-regularization-for-linear-sampling-methods-ex5GQzD2x0

References (10)

Publisher
Springer Journals
Copyright
Copyright © 2009 by Springer Science+Business Media B.V.
Subject
Mathematics; Mechanics; Statistical Physics, Dynamical Systems and Complexity; Theoretical, Mathematical and Computational Physics; Computer Science, general; Mathematics, general
ISSN
0167-8019
eISSN
1572-9036
DOI
10.1007/s10440-009-9558-6
Publisher site
See Article on Publisher Site

Abstract

The problem of determining the shape of an obstacle from far-field measurements is considered. It is well known that linear sampling methods have been widely used for shape reconstructions obtained via the singular system of an ill conditioned discretized far-field operator. For our reconstructions we assume that the far-field data are noisy and we employ a novel regularization method that does not require determination of a regularization parameter.

Journal

Acta Applicandae MathematicaeSpringer Journals

Published: Dec 31, 2009

There are no references for this article.