347 research outputs found
An iterative algorithm for parametrization of shortest length shift registers over finite rings
The construction of shortest feedback shift registers for a finite sequence
S_1,...,S_N is considered over the finite ring Z_{p^r}. A novel algorithm is
presented that yields a parametrization of all shortest feedback shift
registers for the sequence of numbers S_1,...,S_N, thus solving an open problem
in the literature. The algorithm iteratively processes each number, starting
with S_1, and constructs at each step a particular type of minimal Gr\"obner
basis. The construction involves a simple update rule at each step which leads
to computational efficiency. It is shown that the algorithm simultaneously
computes a similar parametrization for the reciprocal sequence S_N,...,S_1.Comment: Submitte
Minimal Polynomial Algorithms for Finite Sequences
We show that a straightforward rewrite of a known minimal polynomial
algorithm yields a simpler version of a recent algorithm of A. Salagean.Comment: Section 2 added, remarks and references expanded. To appear in IEEE
Transactions on Information Theory
Decoding Generalized Reed-Solomon Codes and Its Application to RLCE Encryption Schemes
This paper compares the efficiency of various algorithms for implementing
quantum resistant public key encryption scheme RLCE on 64-bit CPUs. By
optimizing various algorithms for polynomial and matrix operations over finite
fields, we obtained several interesting (or even surprising) results. For
example, it is well known (e.g., Moenck 1976 \cite{moenck1976practical}) that
Karatsuba's algorithm outperforms classical polynomial multiplication algorithm
from the degree 15 and above (practically, Karatsuba's algorithm only
outperforms classical polynomial multiplication algorithm from the degree 35
and above ). Our experiments show that 64-bit optimized Karatsuba's algorithm
will only outperform 64-bit optimized classical polynomial multiplication
algorithm for polynomials of degree 115 and above over finite field
. The second interesting (surprising) result shows that 64-bit
optimized Chien's search algorithm ourperforms all other 64-bit optimized
polynomial root finding algorithms such as BTA and FFT for polynomials of all
degrees over finite field . The third interesting (surprising)
result shows that 64-bit optimized Strassen matrix multiplication algorithm
only outperforms 64-bit optimized classical matrix multiplication algorithm for
matrices of dimension 750 and above over finite field . It should
be noted that existing literatures and practices recommend Strassen matrix
multiplication algorithm for matrices of dimension 40 and above. All our
experiments are done on a 64-bit MacBook Pro with i7 CPU and single thread C
codes. It should be noted that the reported results should be appliable to 64
or larger bits CPU architectures. For 32 or smaller bits CPUs, these results
may not be applicable. The source code and library for the algorithms covered
in this paper are available at http://quantumca.org/
Fast algorithm for border bases of Artinian Gorenstein algebras
Given a multi-index sequence , we present a new efficient algorithm
to compute generators of the linear recurrence relations between the terms of
. We transform this problem into an algebraic one, by identifying
multi-index sequences, multivariate formal power series and linear functionals
on the ring of multivariate polynomials. In this setting, the recurrence
relations are the elements of the kerne l\sigma of the Hankel operator
$H$\sigma associated to . We describe the correspondence between
multi-index sequences with a Hankel operator of finite rank and Artinian
Gorenstein Algebras. We show how the algebraic structure of the Artinian
Gorenstein algebra \sigma\sigma yields the
structure of the terms $\sigma\alpha N nAK[x 1 ,. .. , xnIHIA$ and the tables of multiplication by the variables in these
bases. It is an extension of Berlekamp-Massey-Sakata (BMS) algorithm, with
improved complexity bounds. We present applications of the method to different
problems such as the decomposition of functions into weighted sums of
exponential functions, sparse interpolation, fast decoding of algebraic codes,
computing the vanishing ideal of points, and tensor decomposition. Some
benchmarks illustrate the practical behavior of the algorithm
On Sequences, Rational Functions and Decomposition
Our overall goal is to unify and extend some results in the literature
related to the approximation of generating functions of finite and infinite
sequences over a field by rational functions. In our approach, numerators play
a significant role. We revisit a theorem of Niederreiter on (i) linear
complexities and (ii) ' minimal polynomials' of an infinite sequence,
proved using partial quotients. We prove (i) and its converse from first
principles and generalise (ii) to rational functions where the denominator need
not have minimal degree. We prove (ii) in two parts: firstly for geometric
sequences and then for sequences with a jump in linear complexity. The basic
idea is to decompose the denominator as a sum of polynomial multiples of two
polynomials of minimal degree; there is a similar decomposition for the
numerators. The decomposition is unique when the denominator has degree at most
the length of the sequence. The proof also applies to rational functions
related to finite sequences, generalising a result of Massey. We give a number
of applications to rational functions associated to sequences.Comment: Several more typos corrected. To appear in J. Applied Algebra in
Engineering, Communication and Computing. The final publication version is
available at Springer via http://dx.doi.org/10.1007/s00200-015-0256-
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