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Constants and Darboux Polynomials for Tensor Products of Polynomial Algebras with Derivations

Communications in Algebra, 2004
Let d 1 : k[X] → k[X] and d 2 : k[Y] → k[Y] be k-derivations, where k[X] ≔  k[x 1,…,x n ], k[Y] ≔ k[y 1,…,y m ] are polynomial algebras over a field k of characteristic zero.
Jean Moulin Ollagnier, Andrzej Nowicki
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MOTION PLANNING BY PIECEWISE CONSTANT OR POLYNOMIAL INPUTS

IFAC Proceedings Volumes, 1992
Abstract In this paper we present an algorithmic solution of the “Exact Motion Planning Problem” for nilpotent systems, by piecewise constant or polynomial inputs. By using an identification process, we improve here the solution earlier given by Lafferiere and Sussmann, for systems without drift. So we obtain a much smaller number of pieces (in case
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On Roots and Error Constants of Optimal Stability Polynomials

BIT Numerical Mathematics, 2000
This paper concerns the optimal stability polynomials, which are polynomials whose stability region is as large as possible in a certain region. An important application of these polynomials is the construction of stabilized Runge-Kutta methods. Some properties of the roots of these polynomials are obtained.
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An improved method for estimation of inertia constant of power system based on polynomial approximation

Smart Grid Conference, 2014
M. Shamirzaee   +4 more
semanticscholar   +1 more source

Lebesgue constants in polynomial interpolation

2006
Summary: Lagrange interpolation is a classical method for approximating a continuous function by a polynomial that agrees with the function at a number of chosen points (the 'nodes'). However, the accuracy of the approximation is greatly influenced by the location of these nodes.
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Taylor polynomial solution of hyperbolic type partial differential equations with constant coefficients

International Journal of Computational Mathematics, 2011
Berna Bülbül, M. Sezer
semanticscholar   +1 more source

Derandomizing Polynomial Identity Testing for Multilinear Constant-Read Formulae

2011 IEEE 26th Annual Conference on Computational Complexity, 2011
Matthew W. Anderson   +2 more
semanticscholar   +1 more source

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