English

Computing GCRDs of Approximate Differential Polynomials

Symbolic Computation 2014-07-25 v2 Numerical Analysis

Abstract

Differential (Ore) type polynomials with approximate polynomial coefficients are introduced. These provide a useful representation of approximate differential operators with a strong algebraic structure, which has been used successfully in the exact, symbolic, setting. We then present an algorithm for the approximate Greatest Common Right Divisor (GCRD) of two approximate differential polynomials, which intuitively is the differential operator whose solutions are those common to the two inputs operators. More formally, given approximate differential polynomials ff and gg, we show how to find "nearby" polynomials f~\widetilde f and g~\widetilde g which have a non-trivial GCRD. Here "nearby" is under a suitably defined norm. The algorithm is a generalization of the SVD-based method of Corless et al. (1995) for the approximate GCD of regular polynomials. We work on an appropriately "linearized" differential Sylvester matrix, to which we apply a block SVD. The algorithm has been implemented in Maple and a demonstration of its robustness is presented.

Cite

@article{arxiv.1406.0907,
  title  = {Computing GCRDs of Approximate Differential Polynomials},
  author = {Mark Giesbrecht and Joseph Haraldson},
  journal= {arXiv preprint arXiv:1406.0907},
  year   = {2014}
}

Comments

To appear, Workshop on Symbolic-Numeric Computing (SNC'14) July 2014

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