Hermite normal form computation using modulo determinant arithmetic
Mathematics of Operations Research
A new method for computing a column reduced polynomial matrix
Systems & Control Letters
Algorithms for computer algebra
Algorithms for computer algebra
A Uniform Approach for the Fast Computation of Matrix-Type Pade Approximants
SIAM Journal on Matrix Analysis and Applications
Preconditioning of rectangular polynomial matrices for efficient Hermite normal form computation
ISSAC '95 Proceedings of the 1995 international symposium on Symbolic and algebraic computation
Computing Popov and Hermite forms of polynomial matrices
ISSAC '96 Proceedings of the 1996 international symposium on Symbolic and algebraic computation
Asymptotically fast computation of Hermite normal forms of integer matrices
ISSAC '96 Proceedings of the 1996 international symposium on Symbolic and algebraic computation
Recursiveness in matrix rational interpolation problems
Journal of Computational and Applied Mathematics - Special issue: ROLLS symposium
Fraction-free computation of matrix Padé systems
ISSAC '97 Proceedings of the 1997 international symposium on Symbolic and algebraic computation
Shifted normal forms of polynomial matrices
ISSAC '99 Proceedings of the 1999 international symposium on Symbolic and algebraic computation
Fraction-Free Computation of Matrix Rational Interpolants and Matrix GCDs
SIAM Journal on Matrix Analysis and Applications
Fraction-free row reduction of matrices of skew polynomials
Proceedings of the 2002 international symposium on Symbolic and algebraic computation
On the complexity of polynomial matrix computations
ISSAC '03 Proceedings of the 2003 international symposium on Symbolic and algebraic computation
On lattice reduction for polynomial matrices
Journal of Symbolic Computation
Essentially optimal computation of the inverse of generic polynomial matrices
Journal of Complexity - Special issue: Foundations of computational mathematics 2002 workshops
Output-sensitive modular algorithms for polynomial matrix normal forms
Journal of Symbolic Computation
ACM Communications in Computer Algebra
Efficient computation of order bases
Proceedings of the 2009 international symposium on Symbolic and algebraic computation
Fraction-free row reduction of matrices of Ore polynomials
Journal of Symbolic Computation
Computing hermite forms of polynomial matrices
Proceedings of the 36th international symposium on Symbolic and algebraic computation
Normalization of row reduced matrices
Proceedings of the 36th international symposium on Symbolic and algebraic computation
Triangular x-basis decompositions and derandomization of linear algebra algorithms over K[x]
Journal of Symbolic Computation
Efficient algorithms for order basis computation
Journal of Symbolic Computation
Gröbner walk for computing matrix normal forms over Ore polynomials
ACM Communications in Computer Algebra
Rational invariants of scalings from Hermite normal forms
Proceedings of the 37th International Symposium on Symbolic and Algebraic Computation
Computing minimal nullspace bases
Proceedings of the 37th International Symposium on Symbolic and Algebraic Computation
Computing column bases of polynomial matrices
Proceedings of the 38th international symposium on International symposium on symbolic and algebraic computation
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We present an algorithm for the computation of a shifted Popov normal form of a rectangular polynomial matrix. For specific input shifts, we obtain methods for computing the matrix greatest common divisor of two matrix polynomials (in normal form) and procedures for such polynomial normal form computations as those of the classical Popov form and the Hermite normal form. The method involves embedding the problem of computing shifted forms into one of computing matrix rational approximants. This has the advantage of allowing for fraction-free computations over integral domains such as Z[z] and K[a"1,...,a"n][z]. In the case of rectangular matrix input, the corresponding multipliers for the shifted forms are not unique. We use the concept of minimal matrix approximants to introduce a notion of minimal multipliers and show how such multipliers are computed by our methods.