345 research outputs found
New Set of Codes for the Maximum-Likelihood Decoding Problem
The maximum-likelihood decoding problem is known to be NP-hard for general
linear and Reed-Solomon codes. In this paper, we introduce the notion of
A-covered codes, that is, codes that can be decoded through a polynomial time
algorithm A whose decoding bound is beyond the covering radius. For these
codes, we show that the maximum-likelihood decoding problem is reachable in
polynomial time in the code parameters. Focusing on bi- nary BCH codes, we were
able to find several examples of A-covered codes, including two codes for which
the maximum-likelihood decoding problem can be solved in quasi-quadratic time.Comment: in Yet Another Conference on Cryptography, Porquerolle : France
(2010
Linear-time list recovery of high-rate expander codes
We show that expander codes, when properly instantiated, are high-rate list
recoverable codes with linear-time list recovery algorithms. List recoverable
codes have been useful recently in constructing efficiently list-decodable
codes, as well as explicit constructions of matrices for compressive sensing
and group testing. Previous list recoverable codes with linear-time decoding
algorithms have all had rate at most 1/2; in contrast, our codes can have rate
for any . We can plug our high-rate codes into a
construction of Meir (2014) to obtain linear-time list recoverable codes of
arbitrary rates, which approach the optimal trade-off between the number of
non-trivial lists provided and the rate of the code. While list-recovery is
interesting on its own, our primary motivation is applications to
list-decoding. A slight strengthening of our result would implies linear-time
and optimally list-decodable codes for all rates, and our work is a step in the
direction of solving this important problem
Re-encoding reformulation and application to Welch-Berlekamp algorithm
The main decoding algorithms for Reed-Solomon codes are based on a bivariate
interpolation step, which is expensive in time complexity. Lot of interpolation
methods were proposed in order to decrease the complexity of this procedure,
but they stay still expensive. Then Koetter, Ma and Vardy proposed in 2010 a
technique, called re-encoding, which allows to reduce the practical running
time. However, this trick is only devoted for the Koetter interpolation
algorithm. We propose a reformulation of the re-encoding for any interpolation
methods. The assumption for this reformulation permits only to apply it to the
Welch-Berlekamp algorithm
It'll probably work out: improved list-decoding through random operations
In this work, we introduce a framework to study the effect of random
operations on the combinatorial list-decodability of a code. The operations we
consider correspond to row and column operations on the matrix obtained from
the code by stacking the codewords together as columns. This captures many
natural transformations on codes, such as puncturing, folding, and taking
subcodes; we show that many such operations can improve the list-decoding
properties of a code. There are two main points to this. First, our goal is to
advance our (combinatorial) understanding of list-decodability, by
understanding what structure (or lack thereof) is necessary to obtain it.
Second, we use our more general results to obtain a few interesting corollaries
for list decoding:
(1) We show the existence of binary codes that are combinatorially
list-decodable from fraction of errors with optimal rate
that can be encoded in linear time.
(2) We show that any code with relative distance, when randomly
folded, is combinatorially list-decodable fraction of errors with
high probability. This formalizes the intuition for why the folding operation
has been successful in obtaining codes with optimal list decoding parameters;
previously, all arguments used algebraic methods and worked only with specific
codes.
(3) We show that any code which is list-decodable with suboptimal list sizes
has many subcodes which have near-optimal list sizes, while retaining the error
correcting capabilities of the original code. This generalizes recent results
where subspace evasive sets have been used to reduce list sizes of codes that
achieve list decoding capacity
List-Decoding of Binary Goppa Codes up to the Binary Johnson Bound
International audienceWe study the list-decoding problem of alternant codes (which includes obviously that of classical Goppa codes). The major consideration here is to take into account the (small) size of the alphabet. This amounts to comparing the generic Johnson bound to the q-ary Johnson bound. The most favourable case is q = 2, for which the decoding radius is greatly improved. Even though the announced result, which is the list-decoding radius of binary Goppa codes, is new, we acknowledge that it can be made up from separate previous sources, which may be a little bit unknown, and where the binary Goppa codes has apparently not been thought at. Only D. J. Bernstein has treated the case of binary Goppa codes in a preprint. References are given in the introduction. We propose an autonomous and simplified treatment and also a complexity analysis of the studied algorithm, which is quadratic in the blocklength n, when decoding away of the relative maximum decoding radius
An algorithm for list decoding number field codes
We present an algorithm for list decoding codewords of algebraic number field codes in polynomial time. This is the first explicit procedure for decoding number field codes whose construction were previously described by Lenstra [12] and Guruswami [8]. We rely on a new algorithm for computing the Hermite normal form of the basis of an OK -module due to Biasse and Fieker [2] where OK is the ring of integers of a number field K
Hamming Approximation of NP Witnesses
Given a satisfiable 3-SAT formula, how hard is it to find an assignment to
the variables that has Hamming distance at most n/2 to a satisfying assignment?
More generally, consider any polynomial-time verifier for any NP-complete
language. A d(n)-Hamming-approximation algorithm for the verifier is one that,
given any member x of the language, outputs in polynomial time a string a with
Hamming distance at most d(n) to some witness w, where (x,w) is accepted by the
verifier. Previous results have shown that, if P != NP, then every NP-complete
language has a verifier for which there is no
(n/2-n^(2/3+d))-Hamming-approximation algorithm, for various constants d > 0.
Our main result is that, if P != NP, then every paddable NP-complete language
has a verifier that admits no (n/2+O(sqrt(n log n)))-Hamming-approximation
algorithm. That is, one cannot get even half the bits right. We also consider
natural verifiers for various well-known NP-complete problems. They do have
n/2-Hamming-approximation algorithms, but, if P != NP, have no
(n/2-n^epsilon)-Hamming-approximation algorithms for any constant epsilon > 0.
We show similar results for randomized algorithms
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