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Differential entropy

Known as: Continuous entropy 
Differential entropy (also referred to as continuous entropy) is a concept in information theory that began as an attempt by Shannon to extend the… Expand
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Papers overview

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Highly Cited
2014
Highly Cited
2014
A bstractRecently it has been shown that the Bekenstein-Hawking entropy formula evaluated on certain closed surfaces in the bulk… Expand
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Highly Cited
2013
Highly Cited
2013
EEG-based emotion recognition has been studied for a long time. In this paper, a new effective EEG feature named differential… Expand
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Highly Cited
2009
Highly Cited
2009
In this paper, an entropy-consistent flux is developed, continuing from the work of the previous paper. To achieve entropy… Expand
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Highly Cited
2008
Highly Cited
2008
For many practical probability density representations such as for the widely used Gaussian mixture densities, an analytic… Expand
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Highly Cited
2005
Highly Cited
2005
We study the problem of maximum entropy density estimation in the presence of known sample selection bias. We propose three bias… Expand
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Highly Cited
2003
Highly Cited
2003
We present a conceptually simple method for hierarchical clustering of data called mutual information clustering (MIC) algorithm… Expand
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Review
1997
Review
1997
We assume that H(f) is well-defined and is finite. The concept of differential entropy was introduced in Shannon’s original paper… Expand
Highly Cited
1997
Highly Cited
1997
We derive a first-order approximation of the density of maximum entropy for a continuous 1-D random variable, given a number of… Expand
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Review
1991
Review
1991
Preface to the Second Edition. Preface to the First Edition. Acknowledgments for the Second Edition. Acknowledgments for the… Expand
Highly Cited
1978
Highly Cited
1978
A table is given of differential entropies for various continuous probability distributions. The formulas, some of which are new… Expand