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Computing the Rank and a Small Nullspace Basis of a Polynomial Matrix (2005)

Abstract
We reduce the problem of computing the rank and a nullspace basis of a univariate polynomial matrix to polynomial matrix multiplication. For an input n x n matrix of degree d over a field K we give a rank and nullspace algorithm using about the same number of operations as for multiplying two matrices of dimension n and degree d. If the latter multiplication is done in MM(n,d)=softO(n^omega d) operations, with omega the exponent of matrix multiplication over K, then the algorithm uses softO(MM(n,d)) operations in K. The softO notation indicates some missing logarithmic factors. The method is randomized with Las Vegas certification. We achieve our results in part through a combination of matrix Hensel high-order lifting and matrix minimal fraction reconstruction, and through the computation of minimal or small degree vectors in the nullspace seen as a K[x]-module

Publication details
Download http://hal.ccsd.cnrs.fr/ccsd-00004832/en/
Source http://hal.ccsd.cnrs.fr/docs/00/03/04/23/PDF/basis.pdf
Publisher HAL - CCSd - CNRS
Contributors Gilles Villard
Repository CCSd/HAL : e-articles server (based on gBUS) (France)
Keywords Cognitive science/Computer science, Computer Science/Symbolic Computation, Computer Science/Computational Complexity
Type ARTCOLLOQUE
Language Englisch
Coverage linear algebra:polynomial matrix:matrix rank:nullspace basis:minimal polynomial basis

Publications citing this publication (1)
Asymptotically fast polynomial matrix algorithms for multivariable systems (2005)

Cited publications (1)
On Lattice Reduction for Polynomial Matrices (2001)