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MaxEnt Upper Bounds for the Differential Entropy of Univariate Continuous Distributions

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Date

2017

Authors

Nielsen, Frank
Nock, Richard

Journal Title

Journal ISSN

Volume Title

Publisher

Institute of Electrical and Electronics Engineers (IEEE Inc)

Abstract

We present a series of closed-form upper bounds of the differential entropy of univariate continuous distributions based on the maximum entropy principle. We apply those bounds to Gaussian mixture models, and study their tightness properties

Description

Keywords

Absolute geometric moment, absolute monomial exponential family (EF), differential entropy, maximum entropy principle, mixture model

Citation

URI

http://hdl.handle.net/1885/242821

Collections

ANU Research Publications

Source

IEEE Signal Processing Letters

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

DOI

10.1109/LSP.2017.2666792

Restricted until

2099-12-31

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01_Nielsen_MaxEnt_Upper_Bounds_for_the_2017.pdf (125.02 KB)

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