In coding theory, a Tanner graph is a bipartite graph that can be used to express constraints (typically equations) that specify an error correcting code. Tanner graphs play a central role in the design and decoding of LDPC codes. They have also been applied to the construction of longer codes from smaller ones. Both encoders and decoders employ these graphs extensively.
Tanner graphs were proposed by Michael Tanner [1] as a means to create larger error correcting codes from smaller ones using recursive techniques. He generalized the techniques of Elias for product codes.
Tanner discussed lower bounds on the codes obtained from these graphs irrespective of the specific characteristics of the codes which were being used to construct larger codes.
Tanner graphs are partitioned into subcode nodes and digit nodes. For linear block codes, the subcode nodes denote rows of the parity-check matrix H. The digit nodes represent the columns of the matrix H. An edge connects a subcode node to a digit node if a nonzero entry exists in the intersection of the corresponding row and column.
Tanner proved the following bounds
Let be the rate of the resulting linear code, let the degree of the digit nodes be and the degree of the subcode nodes be . If each subcode node is associated with a linear code (n,k) with rate r = k/n, then the rate of the code is bounded by
The advantage of these recursive techniques is that they are computationally tractable. The coding algorithm for Tanner graphs is extremely efficient in practice, although it is not guaranteed to converge except for cycle-free graphs, which are known not to admit asymptotically good codes. [2]
Zemor's decoding algorithm, which is a recursive low-complexity approach to code construction, is based on Tanner graphs.
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In coding theory, Zemor's algorithm, designed and developed by Gilles Zemor, is a recursive low-complexity approach to code construction. It is an improvement over the algorithm of Sipser and Spielman.
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A galactic algorithm is an algorithm with record-breaking theoretical (asymptotic) performance, but which isn't used due to practical constraints. Typical reasons are that the performance gains only appear for problems that are so large they never occur, or the algorithm's complexity outweighs a relatively small gain in performance. Galactic algorithms were so named by Richard Lipton and Ken Regan, because they will never be used on any data sets on Earth.
