Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification

被引：0

作者：

M. M. Lange

A. M. Lange

机构：

[1] Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences,

来源：

Pattern Recognition and Image Analysis | 2022年 / 32卷

关键词：

source coding; object classification; error probability; mutual information; observation channel; Hamming distortion measure; rate-distortion function; lower bound;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

引用

页码：570 / 574

页数：4

共 8 条

[1] Information-Theoretic Lower Bounds to Error Probability for the Models of Noisy Discrete Source Coding and Object Classification
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