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Type: Artigo de periódico
Title: A cheaper way to compute generalized cross-validation as a stopping rule for linear stationary iterative methods
Author: Santos, RJ
De Pierro, AR
Abstract: We apply generalized cross-validation (GCV) as a stopping rule for general linear stationary iterative methods for solving very large-scale, ill-conditioned problems. We present a new general formula for the influence operator for these methods and, using this formula and a Monte Carlo approach, we show how to compute the GCV function at a cheaper cost. Then we apply our approach to a well known iterative method (ART) with simulated data in positron emission tomography (PET).
Subject: emission tomography
ill-posed problems
parameter estimation
Country: EUA
Editor: Amer Statistical Assoc
Rights: fechado
Identifier DOI: 10.1198/1061860031815
Date Issue: 2003
Appears in Collections:Unicamp - Artigos e Outros Documentos

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