An Alternative to Tikhonov Regularization for Linear Sampling Methods

  • Authors:
  • K. Kim;K. H. Leem;G. Pelekanos

  • Affiliations:
  • Department of Mathematics, Yeungnam University, Gyeongsangbuk-do, South Korea 719-749;Department of Mathematics and Statistics, Southern Illinois University, Edwardsville, USA 62026;Department of Mathematics and Statistics, Southern Illinois University, Edwardsville, USA 62026

  • Venue:
  • Acta Applicandae Mathematicae: an international survey journal on applying mathematics and mathematical applications
  • Year:
  • 2010

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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.