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Proceedings Paper

On The Acceleration Of Maximum Likelihood Algorithms
Author(s): Charles E. Metz; Chin-Tu Chen
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Paper Abstract

Maximum likelihood algorithms have the potential of producing improved estimates with high accuracy. The computational requirements often become prohibitively expensive, however, because of the slow rates of convergence of these algorithms. This paper discusses three classes of acceleration techniques by which convergence to the maximum likelihood solution can be sped up. Some characteristics of these acceleration methods are examined.

Paper Details

Date Published: 27 June 1988
PDF: 6 pages
Proc. SPIE 0914, Medical Imaging II, (27 June 1988); doi: 10.1117/12.968650
Show Author Affiliations
Charles E. Metz, The University of Chicago (United States)
Chin-Tu Chen, The University of Chicago (United States)

Published in SPIE Proceedings Vol. 0914:
Medical Imaging II
Samuel J. Dwyer; Roger H. Schneider; Samuel J. Dwyer; Roger H. Schneider; Roger H. Schneider; Samuel J. Dwyer, Editor(s)

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