Design of Optimal Entropy-constrained Scalar Quantizer for Sequential Coding of Correlated Sources

被引：0

作者：

Wu, Huihui ^{[1
]}

Dumitrescu, Sorina ^{[1
]}

机构：

[1] McMaster Univ, Dept Elect & Comp Engn, Hamilton, ON, Canada

来源：

2017 IEEE INFORMATION THEORY WORKSHOP (ITW) | 2017年

关键词：

Sequential coding; scalar quantization; entropy-constrained; globally optimal algorithm; minimum weight path problem; LOCALLY OPTIMAL QUANTIZER; UNIQUENESS;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

This work addresses the design of a sequential code for correlated sources using entropy-constrained scalar quantization at each encoder. We consider discrete sources and propose a globally optimal algorithm to minimize a weighted sum of distortions and rates. Our algorithm is based on solving the minimum weight path problem in a series of appropriately constructed weighted directed acyclic graphs. Its asymptotical time complexity is O((N1N22)-N-2), where N-1 and N-2 denote the alphabet sizes of the two sources, respectively.

引用

页码：524 / 528

页数：5

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