Identification Capacity of Correlation-Assisted Discrete Memoryless Channels: Analytical Properties and Representations
Research output: Contribution to book/Conference proceedings/Anthology/Report › Conference contribution › Contributed › peer-review
Contributors
Abstract
The problem of identification is considered, in which it is of interest for the receiver to decide only whether a certain message has been sent or not. Identification via correlation-assisted discrete memoryless channels is studied, where the transmitter and the receiver further have access to correlated source observations. Analytical properties and representations of the corresponding identification capacity are studied. In this paper, it is shown that the identification capacity cannot be represented as a maximization of a single-letter (or multi-letter with fixed length) expression of entropic quantities. Further, it is shown that the identification capacity is not Banach-Mazur computable and therewith not Turing computable. Consequently, there is no algorithm that can simulate or compute the identification capacity, even if there are no limitations on computational complexity and computing power.
Details
Original language | English |
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Title of host publication | 2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 470-474 |
Number of pages | 5 |
ISBN (electronic) | 978-1-5386-9291-2 |
Publication status | Published - Jul 2019 |
Peer-reviewed | Yes |
Externally published | Yes |
Publication series
Series | IEEE International Symposium on Information Theory |
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Volume | 2019-July |
ISSN | 2157-8095 |
Conference
Title | 2019 IEEE International Symposium on Information Theory, ISIT 2019 |
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Duration | 7 - 12 July 2019 |
City | Paris |
Country | France |
External IDs
ORCID | /0000-0002-1702-9075/work/165878304 |
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