DocumentCode
3112504
Title
Estimation of the entropy on the basis of its polynomial representation
Author
Vinck, Martin ; Battaglia, Francesco P. ; Balakirsky, Vladimir B. ; Vinck, A. J Han ; Pennartz, Cyriel
Author_Institution
Center for Neurosci., Univ. of Amsterdam, Amsterdam, Netherlands
fYear
2012
fDate
1-6 July 2012
Firstpage
1054
Lastpage
1058
Abstract
An algorithm for estimating the entropy, which is based on the representation of the entropy function as the sum of two polynomial terms, called the polynomial approximation function and the remainder, is proposed. We construct an accurate and unbiased estimate of the value of the polynomial approximation function and use the known Bayesian approach to estimate the remainder. The combined estimator essentially reduces the bias of the constructed estimate as compared to the known estimators. Simulation results that confirm the claim are presented.
Keywords
Bayes methods; entropy; neurophysiology; polynomial approximation; Bayesian approach; discrete memoryless source; entropy estimation; entropy function representation; neurophysiology; polynomial approximation function; polynomial representation; remainder estimation; Approximation methods; Bayesian methods; Entropy; Estimation; Polynomials; Probability distribution; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory Proceedings (ISIT), 2012 IEEE International Symposium on
Conference_Location
Cambridge, MA
ISSN
2157-8095
Print_ISBN
978-1-4673-2580-6
Electronic_ISBN
2157-8095
Type
conf
DOI
10.1109/ISIT.2012.6283012
Filename
6283012
Link To Document