Rate Distortion Theory with Generalized Information Measures via Convex Programming Duality

Aharon Ben-Tal; Marc Teboulle

doi:10.1109/TIT.1986.1057223

Rate Distortion Theory with Generalized Information Measures via Convex Programming Duality

Aharon Ben-Tal, Marc Teboulle

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

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Abstract

A new generalized average mutual information measure (GAMIM) is introduced in terms of Csiszar ϕ-divergence, and the associated rate distortion function R_ϕ is studied. The main objective is to derive in a unified way a dual representation of R_ϕ then to use it to generalize classical results (corresponding to ϕ(t) = t log t) in rate distortion theory and extend results associated with other concepts of GAMIM. Our development uses the methodology of convex programming duality extensively.

Original language	English
Pages (from-to)	630-641
Number of pages	12
Journal	IEEE Transactions on Information Theory
Volume	32
Issue number	5
DOIs	https://doi.org/10.1109/TIT.1986.1057223
State	Published - Sep 1986
Externally published	Yes

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10.1109/TIT.1986.1057223

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Rate Distortion Theory with Generalized Information Measures via Convex Programming Duality

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