A unifying variational perspective on some fundamental information theoretic inequalities

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This paper proposes a unifying variational approach for proving and extending some fundamental information theoretic inequalities. Fundamental information theory results such as maximization of differential entropy, minimization of Fisher information (Cramér-Rao inequality), worst additive noise lemma, entropy power inequality, and extremal entropy inequality are interpreted as functional problems and proved within the framework of calculus of variations. Several applications and possible extensions of the proposed results are briefly mentioned.

Original languageEnglish
Article number6566200
Pages (from-to)7132-7148
Number of pages17
JournalIEEE Transactions on Information Theory
Issue number11
Publication statusPublished - 4 Nov 2013



  • Maximizing entropy
  • calculus of variations
  • entropy power inequality
  • extremal entropy inequality
  • minimizing Fisher information
  • worst additive noise

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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