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General nonasymptotic and asymptotic formulas in channel resolvability and identification capacity and their application to the wiretap channel

Masahito Hayashi
- 01 Apr 2006 - 
- Vol. 52, Iss: 4, pp 1562-1575
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TLDR
Several nonasymptotic formulas are established in channel resolvability and identification capacity and they are applied to the wiretap channel, and lower bounds of the exponents of error probability and the wiretapper's information in the wiretAP channel are obtained.
Abstract
Several nonasymptotic formulas are established in channel resolvability and identification capacity, and they are applied to the wiretap channel. By using these formulas, the epsi capacities of the above three problems are considered in the most general setting, where no structural assumptions such as the stationary memoryless property are made on a channel. As a result, we solve an open problem proposed by Han and Verduacute. Moreover, we obtain lower bounds of the exponents of error probability and the wiretapper's information in the wiretap channel

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References
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Journal ArticleDOI

The wire-tap channel

TL;DR: This paper finds the trade-off curve between R and d, assuming essentially perfect (“error-free”) transmission, and implies that there exists a Cs > 0, such that reliable transmission at rates up to Cs is possible in approximately perfect secrecy.
Book

Information Theory and Reliable Communication

TL;DR: This chapter discusses Coding for Discrete Sources, Techniques for Coding and Decoding, and Source Coding with a Fidelity Criterion.
Journal ArticleDOI

Information Theory and Reliable Communication

D.A. Bell
Journal ArticleDOI

A general formula for channel capacity

TL;DR: A formula for the capacity of arbitrary single-user channels without feedback is proved and capacity is shown to equal the supremum, over all input processes, of the input-output inf-information rate defined as the liminf in probability of the normalized information density.
Book

Information-Spectrum Methods in Information Theory

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TL;DR: This paper presents a meta-analyses of source and channel coding for multi-Terminal Information Theory, which aims to clarify the role of symbols in the development of information theory.