Regularization of multiplicative iterative algorithms with nonnegative constraint (Articolo in rivista)

Type
Label
  • Regularization of multiplicative iterative algorithms with nonnegative constraint (Articolo in rivista) (literal)
Anno
  • 2014-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1088/0266-5611/30/3/035012 (literal)
Alternative label
  • Benvenuto, Federico; Piana, Michele (2014)
    Regularization of multiplicative iterative algorithms with nonnegative constraint
    in Inverse problems (Print)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Benvenuto, Federico; Piana, Michele (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 30 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
  • 17 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 3 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • University of Genoa; CNR SPIN (literal)
Titolo
  • Regularization of multiplicative iterative algorithms with nonnegative constraint (literal)
Abstract
  • This paper studies the regularization of the constrained maximum likelihood iterative algorithms applied to incompatible ill-posed linear inverse problems. Specifically, we introduce a novel stopping rule which defines a regularization algorithm for the iterative space reconstruction algorithm in the case of least-squares minimization. Further we show that the same rule regularizes the expectation maximization algorithm in the case of Kullback-Leibler minimization, provided a well-justified modification of the definition of Tikhonov regularization is introduced. The performances of this stopping rule are illustrated in the case of an image reconstruction problem in the x-ray solar astronomy. (literal)
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