Data processing using information theory functionals

Rallis C. Papademetriou

doi:10.1108/03684929810209478

Data processing using information theory functionals

Rallis C. Papademetriou^*

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

Abstract

This paper presents an overview of three information‐theoretic methods, which have been used extensively in many areas such as signal/image processing, pattern recognition and statistical inference. These are: the maximum entropy (ME), minimum cross‐entropy (MCE) and mutual information (MI) methods. The development history of these techniques is reviewed, their essential philosophy is explained, and typical applications, supported by simulation results, are discussed.

Original language	English
Pages (from-to)	264-272
Number of pages	9
Journal	Kybernetes
Volume	27
Issue number	3
DOIs	https://doi.org/10.1108/03684929810209478
Publication status	Published - 1 Apr 1998

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title = "Data processing using information theory functionals",

abstract = "This paper presents an overview of three information‐theoretic methods, which have been used extensively in many areas such as signal/image processing, pattern recognition and statistical inference. These are: the maximum entropy (ME), minimum cross‐entropy (MCE) and mutual information (MI) methods. The development history of these techniques is reviewed, their essential philosophy is explained, and typical applications, supported by simulation results, are discussed.",

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AB - This paper presents an overview of three information‐theoretic methods, which have been used extensively in many areas such as signal/image processing, pattern recognition and statistical inference. These are: the maximum entropy (ME), minimum cross‐entropy (MCE) and mutual information (MI) methods. The development history of these techniques is reviewed, their essential philosophy is explained, and typical applications, supported by simulation results, are discussed.

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EP - 272

JO - Kybernetes

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Data processing using information theory functionals

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