Accelerated, Sparsity-Aware Generalizations of Classical Algorithms for TomoPIV - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2015

Accelerated, Sparsity-Aware Generalizations of Classical Algorithms for TomoPIV

Abstract

We set up a generalized optimization framework for the classical Row Action Methods, otherwise customarily employed in the TomoPIV community. This scheme allows us to bypass known caveats of the algebraic programs. The so-enhance methods enable i) handling explicit constraints on the signal; ii) accelerating the rates of convergence. Comparative numerical simulations reveal superior performance of the latter with no inflation of the complexity.
Fichier principal
Vignette du fichier
Barbu2015a.pdf (189.51 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01245014 , version 1 (16-12-2015)
hal-01245014 , version 2 (22-02-2016)

Identifiers

  • HAL Id : hal-01245014 , version 2

Cite

Ioana Barbu, Cédric Herzet. Accelerated, Sparsity-Aware Generalizations of Classical Algorithms for TomoPIV. PIV15, The 11th International Symposium on Particle Image Velocimetry, Sep 2015, Santa Barbara, California, United States. ⟨hal-01245014v2⟩
194 View
109 Download

Share

Gmail Facebook X LinkedIn More