MyJournals Home  

RSS FeedsEntropy, Vol. 19, Pages 232: A Kullback-Leibler View of Maximum Entropy and Maximum Log-Probability Methods (Entropy)

 
 

19 may 2017 09:17:49

 
Entropy, Vol. 19, Pages 232: A Kullback-Leibler View of Maximum Entropy and Maximum Log-Probability Methods (Entropy)
 


Entropy methods enable a convenient general approach to providing a probability distribution with partial information. The minimum cross-entropy principle selects the distribution that minimizes the Kullback-Leibler divergence subject to the given constraints. This general principle encompasses a wide variety of distributions, and generalizes other methods that have been proposed independently. There remains, however, some confusion about the breadth of entropy methods in the literature. In particular, the asymmetry of the Kullback-Leibler divergence provides two important special cases when the target distribution is uniform: the maximum entropy method and the maximum log-probability method. This paper compares the performance of both methods under a variety of conditions. We also examine a generalized maximum log-probability method as a further demonstration of the generality of the entropy approach.


 
89 viewsCategory: Informatics, Physics
 
Entropy, Vol. 19, Pages 231: A Novel Faults Diagnosis Method for Rolling Element Bearings Based on EWT and Ambiguity Correlation Classifiers (Entropy)
Entropy, Vol. 19, Pages 234: The Particle as a Statistical Ensemble of Events in Stueckelberg-Horwitz-Piron Electrodynamics (Entropy)
 
 
blog comments powered by Disqus


MyJournals.org
The latest issues of all your favorite science journals on one page

Username:
Password:

Register | Retrieve

Search:

Physics


Copyright © 2008 - 2024 Indigonet Services B.V.. Contact: Tim Hulsen. Read here our privacy notice.
Other websites of Indigonet Services B.V.: Nieuws Vacatures News Tweets Nachrichten