ORCID Profile
0000-0001-6263-7355
Current Organisations
Commonwealth Scientific and Industrial Research Organisation
,
Australia National University
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Publisher: MDPI AG
Date: 16-03-2017
DOI: 10.3390/E19030122
Publisher: Springer International Publishing
Date: 2021
Publisher: MDPI AG
Date: 20-10-2016
DOI: 10.20944/PREPRINTS201610.0086.V1
Abstract: Information-theoretic measures such as the entropy, cross-entropy and the Kullback-Leibler ergence between two mixture models is a core primitive in many signal processing tasks. Since the Kullback-Leibler ergence of mixtures provably does not admit a closed-form formula, it is in practice either estimated using costly Monte-Carlo stochastic integration, approximated, or bounded using various techniques. We present a fast and generic method that builds algorithmically closed-form lower and upper bounds on the entropy, the cross-entropy and the Kullback-Leibler ergence of mixtures. We illustrate the versatile method by reporting on our experiments for approximating the Kullback-Leibler ergence between univariate exponential mixtures, Gaussian mixtures, Rayleigh mixtures, and Gamma mixtures.
Publisher: MDPI AG
Date: 09-12-2016
DOI: 10.3390/E18120442
Publisher: ACM
Date: 17-11-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Location: Australia
Location: Saudi Arabia
No related grants have been discovered for Ke SUN.