On the Multiple Description Coding Problem with One Semi-Deterministic Distortion Measure

Lin Zhou; Mehul Motani

doi:10.1109/GLOCOM.2017.8254245

On the Multiple Description Coding Problem with One Semi-Deterministic Distortion Measure

Lin Zhou
, Mehul Motani

National University of Singapore

Research output: Contribution to journal › Conference article › peer-review

3 Scopus citations

Abstract

In this paper, we revisit the multiple description coding problem with one semi-deterministic distortion measure, which we term as the Fu- Yeung problem (Fu and Yeung, 2002). We present the properties of optimal test channels for the minimum sum-rate function, a non- asymptotic converse bound and second-order asymptotics for discrete memoryless sources. Since the successive refinement problem is a special case of the Fu-Yeung problem, as a by-product, we obtain a non-asymptotic converse bound for the successive refinement problem, which turns out to be a strict generalization of the non-asymptotic converse bound for successively refinable sources (Zhou, Tan and Motani, 2017).

Original language	English
Article number	8254245
Pages (from-to)	1-6
Number of pages	6
Journal	Proceedings - IEEE Global Communications Conference, GLOBECOM
Volume	2018-January
DOIs	https://doi.org/10.1109/GLOCOM.2017.8254245
State	Published - 2017
Externally published	Yes
Event	2017 IEEE Global Communications Conference, GLOBECOM 2017 - Singapore, Singapore Duration: 4 Dec 2017 → 8 Dec 2017

Keywords

Lossy source coding
Multiple description coding
Non-asymptotic converse bound
Second-order asymptotics
Tilted Information Density

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10.1109/GLOCOM.2017.8254245

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title = "On the Multiple Description Coding Problem with One Semi-Deterministic Distortion Measure",

abstract = "In this paper, we revisit the multiple description coding problem with one semi-deterministic distortion measure, which we term as the Fu- Yeung problem (Fu and Yeung, 2002). We present the properties of optimal test channels for the minimum sum-rate function, a non- asymptotic converse bound and second-order asymptotics for discrete memoryless sources. Since the successive refinement problem is a special case of the Fu-Yeung problem, as a by-product, we obtain a non-asymptotic converse bound for the successive refinement problem, which turns out to be a strict generalization of the non-asymptotic converse bound for successively refinable sources (Zhou, Tan and Motani, 2017).",

keywords = "Lossy source coding, Multiple description coding, Non-asymptotic converse bound, Second-order asymptotics, Tilted Information Density",

author = "Lin Zhou and Mehul Motani",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE Global Communications Conference, GLOBECOM 2017 ; Conference date: 04-12-2017 Through 08-12-2017",

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doi = "10.1109/GLOCOM.2017.8254245",

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AU - Motani, Mehul

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AB - In this paper, we revisit the multiple description coding problem with one semi-deterministic distortion measure, which we term as the Fu- Yeung problem (Fu and Yeung, 2002). We present the properties of optimal test channels for the minimum sum-rate function, a non- asymptotic converse bound and second-order asymptotics for discrete memoryless sources. Since the successive refinement problem is a special case of the Fu-Yeung problem, as a by-product, we obtain a non-asymptotic converse bound for the successive refinement problem, which turns out to be a strict generalization of the non-asymptotic converse bound for successively refinable sources (Zhou, Tan and Motani, 2017).

KW - Lossy source coding

KW - Multiple description coding

KW - Non-asymptotic converse bound

KW - Second-order asymptotics

KW - Tilted Information Density

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DO - 10.1109/GLOCOM.2017.8254245

M3 - 会议文章

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JO - Proceedings - IEEE Global Communications Conference, GLOBECOM

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T2 - 2017 IEEE Global Communications Conference, GLOBECOM 2017

Y2 - 4 December 2017 through 8 December 2017

ER -

On the Multiple Description Coding Problem with One Semi-Deterministic Distortion Measure

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Keywords

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