Paper Title:
Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm
  Abstract

The particle swarm optimization (PSO) algorithm is introduced into ghost correction, which is also compared with the NMS algorithm. With linear regression correlation factor as evaluation parameter, it is found that both algorithms have the same quality for model ODF, but when it comes to complicated textures, the PSO algorithm shows high ODF fitting quality. It is also demonstrates that the ghost peaks in the reduced ODF can be excluded out in the true ODF from PSO components with both even and odd terms in the series expansion method.

  Info
Periodical
Materials Science Forum (Volumes 546-549)
Edited by
Yafang Han et al.
Pages
1009-1014
DOI
10.4028/www.scientific.net/MSF.546-549.1009
Citation
J. G. Tang, X. M. Zhang, Y. L. Deng, Z. P. Zhou, "Correction of Ghost in Reduced ODF with Particle Swarm Optimization Algorithm", Materials Science Forum, Vols. 546-549, pp. 1009-1014, 2007
Online since
May 2007
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