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The Basic Theorems of Information Theory
Open accessAbstract
This paper describes briefly the current mathematical models upon which communication theory is based, and presents in some detail an exposition and partial critique of C. E. Shannon's treatment of one such model. It then presents a general limit theorem in the theory of discrete stochastic processes, suggested by a result of Shannon's.
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Cited by
On a measure of the information provided by an experiment
Lindley, D. V. (1956) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177728069 · Cited by 1,509
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Caruso, F., Giovannetti, V., Lupo, C., & Mancini, S. (2012) · arXiv · doi:10.48550/arxiv.1207.5435 · Cited by 331
Localization of the Maximal Entropy Random Walk
Burda, Z., Duda, J., Luck, J. M., & Waclaw, B. (2009) · Physical Review Letters · doi:10.1103/physrevlett.102.160602 · Cited by 187
Metadata
- Authors
- McMillan, B.
- Venue
- The Annals of Mathematical Statistics
- Publisher
- Institute of Mathematical Statistics
- Published
- 1953-06
- Volume
- 24
- Issue
- 2
- Pages
- 196-219
- ISSN
- 0003-4851 (ISSN-L)
- OpenAlex
- W1970091448
- Cited by
- 424
- References
- 0
- FWCI
- 4.69
- Type
- journal article
- Language
- en
- Open access
- bronze
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- McMillan, B. (1953). The Basic Theorems of Information Theory. The Annals of Mathematical Statistics. https://doi.org/10.1214/aoms/1177729028
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
