Efficient numerical approximation of maximum entropy estimates

A class of algorithms for approximation of the maximum entropy estimate of probability density functions on the basis of a finite number of sampled data is introduced. The algorithms are presented as a finite sequence in order of increasing accuracy and decreasing computational efficiency in which t...

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Bibliographic Details
Published in:International journal of control 2006-09, Vol.79 (9), p.1145-1155
Main Authors: Balestrino, A., Caiti, A., Crisostomi, E.
Format: Article
Language:English
Subjects:
Applied sciences
Computer science
control theory
systems
Control theory. Systems
Exact sciences and technology
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Summary:A class of algorithms for approximation of the maximum entropy estimate of probability density functions on the basis of a finite number of sampled data is introduced. The algorithms are presented as a finite sequence in order of increasing accuracy and decreasing computational efficiency in which the last element of the sequence is the exact maximum entropy estimate. Numerical and applicative examples are reported.
ISSN:0020-7179
1366-5820
DOI:10.1080/00207170600818373