Noisy-channel coding theorem
In information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel. This result was presented by Claude Shannon in 1948 and was based in part on earlier work and ideas of Harry Nyquist and Ralph Hartley.
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- enIn information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel. This result was presented by Claude Shannon in 1948 and was based in part on earlier work and ideas of Harry Nyquist and Ralph Hartley.
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- enIn information theory, the noisy-channel coding theorem (sometimes Shannon's theorem or Shannon's limit), establishes that for any given degree of noise contamination of a communication channel, it is possible to communicate discrete data (digital information) nearly error-free up to a computable maximum rate through the channel. This result was presented by Claude Shannon in 1948 and was based in part on earlier work and ideas of Harry Nyquist and Ralph Hartley. The Shannon limit or Shannon capacity of a communication channel refers to the maximum rate of error-free data that can theoretically be transferred over the channel if the link is subject to random data transmission errors, for a particular noise level. It was first described by Shannon (1948), and shortly after published in a book by Shannon and Warren Weaver entitled The Mathematical Theory of Communication (1949). This founded the modern discipline of information theory.
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- projecteuclid.org/download/pdf_1/euclid.ijm/1255380682
- www.inference.phy.cam.ac.uk/mackay/itila/book.html
- cnx.org/content/m10180/latest/
- www.cs.miami.edu/home/burt/learning/Csc524.142/LarsTelektronikk02.pdf
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- Additive white Gaussian noise
- Amiel Feinstein
- Asymptotic equipartition property
- Binary entropy function
- Cambridge University Press
- Category:Coding theory
- Category:Information theory
- Category:Telecommunication theory
- Category:Theorems in discrete mathematics
- Channel capacity
- Claude E. Shannon
- Claude Shannon
- Code
- Code rate
- Data storage device
- David J.C. MacKay
- Digital signal processors
- Error-correcting code
- Error exponent
- Fano
- Fano's inequality
- Fano's Inequality
- Harry Nyquist
- IEEE Transactions on Information Theory
- Information
- Information theory
- John Wiley & Sons
- Lim inf
- Low-density parity-check code
- MIT Press
- Mutual information
- Probability of error
- Ralph Hartley
- Rate–distortion theory
- Reed–Solomon code
- Sampling theorem
- Shannon's source coding theorem
- Shannon–Hartley theorem
- The Mathematical Theory of Communication
- Thomas M. Cover
- Turbo code
- Warren Weaver
- Wolfowitz
- SameAs
- 2D4MP
- Kanali kodeerimise teoreem
- m.09ffjc
- Noisy-channel coderings theorema
- Noisy-channel coding theorem
- Q2345282
- Secondo teorema di Shannon
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- Теоремы Шеннона для канала с шумами
- Շենոնի թեորեմներ
- نظرية تكويد القناة الصاخبة
- シャノンの通信路符号化定理
- 有噪信道编码定理
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- Category:Coding theory
- Category:Information theory
- Category:Telecommunication theory
- Category:Theorems in discrete mathematics
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