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Improved Random-Binning Exponent for Distributed Hypothesis Testing

delete2025-11-01
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PRE
AI
Y
Yuval Kochman
王立功 封面图
王立功 (Ligong Wang) *
DOI:10.1109/TIT.2025.3603269delete
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摘要

摘要

En 中文
Consider the problem of distributed binary hypothesis testing with two terminals, where the decision is made at one of them (the receiver). We study the exponent of the error probability of the second type. Previously, an achievable exponent was derived by Shimokawa, Han, and Amari using a quantization and binning scheme. We propose a simple modification on the receiver's decision rule in this scheme to attain a better exponent.
Keyword:
Receivers
Error probability
Testing
Indexes
IP networks
Observers
Mutual information
Training
Electronic mail
Decoding
Binning
distributed hypothesis testing
error exponent

期刊

I
IEEE Transactions on Information Theory
IF:
2.9
论文数:
317
被引数:
0

机构

S
swiss federal institutes of technology domain
学者数:
9.0W
论文数: 8.0W
被引数: 163
H
hebrew university of jerusalem
学者数:
2.5K
论文数: 1.1K
被引数: 0
引用论文

引用论文

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Elements of Information Theory
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IF0
err2001-10-05
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errThomas M. Cover; Joy A. Thomas
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