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Parameter selection methods for axisymmetric flame tomography through Tikhonov regularization.
Akesson, Emil O; Daun, Kyle J.
Afiliação
  • Akesson EO; Division of Combustion Physics, Lund Institute of Technology, Lund, Sweden.
Appl Opt ; 47(3): 407-16, 2008 Jan 20.
Article em En | MEDLINE | ID: mdl-18204728
Deconvolution of optically collected axisymmetric flame data is equivalent to solving an ill-posed problem subject to severe error amplification. Tikhonov regularization has recently been shown to be well suited for stabilizing this deconvolution, although the success of this method hinges on choosing a suitable regularization parameter. Incorporating a parameter selection scheme transforms this technique into a reliable automatic algorithm that outperforms unregularized deconvolution of a smoothed data set, which is currently the most popular way to analyze axisymmetric data. We review the discrepancy principle, L-curve curvature, and generalized cross-validation parameter selection schemes and conclude that the L-curve curvature algorithm is best suited to this problem.
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Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Appl Opt Ano de publicação: 2008 Tipo de documento: Article País de afiliação: Suécia País de publicação: Estados Unidos
Buscar no Google
Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Appl Opt Ano de publicação: 2008 Tipo de documento: Article País de afiliação: Suécia País de publicação: Estados Unidos