Fast parallel computation of hermite and smith forms of polynomial matrices
SIAM Journal on Algebraic and Discrete Methods
Algorithms for computing a Hermite reduction of a matrix with polynomial coefficients
Theoretical Computer Science
Generalized subresultants for computing the Smith normal form of polynomial matrices
Journal of Symbolic Computation
A modular algorithm for computing greatest common right divisors of Ore polynomials
ISSAC '97 Proceedings of the 1997 international symposium on Symbolic and algebraic computation
A subresultant theory for Ore polynomials with applications
ISSAC '98 Proceedings of the 1998 international symposium on Symbolic and algebraic computation
On solutions of linear functional systems
Proceedings of the 2001 international symposium on Symbolic and algebraic computation
FFT-like multiplication of linear differential operators
Journal of Symbolic Computation
On lattice reduction for polynomial matrices
Journal of Symbolic Computation
Modern Computer Algebra
Algorithms for normal forms for matrices of polynomials and ore polynomials
Algorithms for normal forms for matrices of polynomials and ore polynomials
Products of ordinary differential operators by evaluation and interpolation
Proceedings of the twenty-first international symposium on Symbolic and algebraic computation
Fraction-free row reduction of matrices of Ore polynomials
Journal of Symbolic Computation
On simultaneous row and column reduction of higher-order linear differential systems
Journal of Symbolic Computation
A polynomial-time algorithm for the jacobson form of a matrix of ore polynomials
CASC'12 Proceedings of the 14th international conference on Computer Algebra in Scientific Computing
Gröbner walk for computing matrix normal forms over Ore polynomials
ACM Communications in Computer Algebra
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Given a matrix over the ring of differential polynomials, we show how to compute the Hermite form H of A and a unimodular matrix U such that UA = H . The algorithm requires a polynomial number of operations in F in terms of n , , . When F = *** it require time polynomial in the bit-length of the rational coefficients as well.