Data processing using information theory functionals

Rallis C. Papademetriou*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-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 languageEnglish
    Pages (from-to)264-272
    Number of pages9
    JournalKybernetes
    Volume27
    Issue number3
    DOIs
    Publication statusPublished - 1 Apr 1998

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