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{{Expert-
In [[coding theory]], '''decoding''' is the process of translating received messages into [[codewords]] of a given [[code]]. There have been many common methods of mapping messages to codewords. These are often used to recover messages sent over a [[noisy channel]], such as a [[binary symmetric channel]].
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==Maximum likelihood decoding==
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Given a received codeword <math>x \in \mathbb{F}_2^n</math> '''[[maximum likelihood]] decoding''' picks a codeword <math>y \in C</math> that [[Optimization (mathematics)|maximize]]s
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As with ideal observer decoding, a convention must be agreed to for non-unique decoding.
The maximum likelihood decoding problem can also be modeled as an [[integer programming]] problem.<ref name = feldman>{{cite
The maximum likelihood decoding algorithm is an instance of the "marginalize a product function" problem which is solved by applying the [[generalized distributive law]].<ref name=GenDistLaw>{{cite journal | last1=Aji | first1=Srinivas M. | last2=McEliece | first2=Robert J. | title=The Generalized Distributive Law | journal=IEEE Transactions on Information Theory |date=March 2000 | volume=46 | issue=2 | pages=325–343 | doi=10.1109/18.825794}}</ref>
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* {{cite book | last=Hill | first=Raymond | title=A first course in coding theory | publisher=[[Oxford University Press]] | series=Oxford Applied Mathematics and Computing Science Series | year=1986 | isbn=0-19-853803-0 }}
* {{cite book | last = Pless | first = Vera | authorlink=Vera Pless | title = Introduction to the theory of error-correcting codes | publisher = [[John Wiley & Sons]]|series = Wiley-Interscience Series in Discrete Mathematics | year = 1982| isbn = 0-471-08684-3 }}
* {{cite book | author=J.H. van Lint | title=Introduction to Coding Theory | edition=2nd
== References ==
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