Abstract
Estimating Entropies is Important in Many Fields Including Statistical Physics, Machine Learning and Statistics. While the Shannon Logarithmic Entropy is the Most Fundamental, Other Rényi Entropies Are Also of Importance. in This Paper, We Derive a Bias Corrected Estimator for a Subset of Rényi Entropies. the Advantage of the Estimator is Demonstrated Via Theoretical and Experimental Considerations. © 2009 IEEE.
Recommended Citation
E. Liitiäinen et al., "On the Statistical Estimation of Rényi Entropies," Machine Learning for Signal Processing XIX - Proceedings of the 2009 IEEE Signal Processing Society Workshop, MLSP 2009, article no. 5306242, Institute of Electrical and Electronics Engineers, Dec 2009.
The definitive version is available at https://doi.org/10.1109/MLSP.2009.5306242
Department(s)
Engineering Management and Systems Engineering
International Standard Book Number (ISBN)
978-142444948-4
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Institute of Electrical and Electronics Engineers, All rights reserved.
Publication Date
01 Dec 2009
