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Early Termination in Parametric Linear System Solving and Rational Function Vector Recovery with Error Correction

Published: 23 July 2017 Publication History

Abstract

Consider solving a black box linear system, A(u) x = b(u), where the entries are polynomials in u over a field K, and A(u) is full rank. The solution, x = 1/g(u) f(u), where g is always the least common monic denominator, can be found by evaluating the system at distinct points ξl in K. The solution can be recovered even if some evaluations are erroneous. In [Boyer and Kaltofen, Proc. SNC 2014] the problem is solved with an algorithm that generalizes Welch/Berlekamp decoding of an algebraic Reed-Solomon code. Their algorithm requires the sum of a degree bound for the numerators plus a degree bound for the denominator of the solution. It is possible that the degree bounds input to their algorithm grossly overestimate the actual degrees. We describe an algorithm that given the same inputs uses possibly fewer evaluations to compute the solution. We introduce a second count for the number of evaluations required to recover the solution based on work by Stanley Cabay. The Cabay count includes bounds for the highest degree polynomial in the coefficient matrix and right side vector, but does not require solution degree bounds. Instead our algorithm iterates until the Cabay termination criterion is reached. At this point our algorithm returns the solution. Assuming we have the actual degrees for all necessary input parameters, we give the criterion that determines when the Cabay count is fewer than the generalized Welch/Berlekamp count.
Incorporating our two counts we develop a combined early termination algorithm. We then specialize the algorithm in [Boyer and Kaltofen, Proc. SNC 2014] for parametric linear system solving to the recovery of a vector of rational functions, 1/g(u) f(u), from its evaluations. Thus, if the rational function vector is the solution to a full rank linear system our early termination strategy applies and we may recover it from fewer evaluations than generalized Welch/Berlekamp decoding. If we allow evaluations at poles (roots of g) there are examples where the Cabay count is not sufficient to recover the rational function vector from just its evaluations. This problem is solved if in addition to indicating that an evaluation point is a pole, the black box gives information about the numerators of the solution at the evaluation point.

References

[1]
Daniel Bleichenbacher, Aggelos Kiayias, and Moti Yung. 2003. Decoding of interleaved Reed Solomon codes over noisy data. In International Colloquium on Automata, Languages, and Programming. Springer, 97--108.
[2]
Brice B. Boyer and Erich Kaltofen. 2014. Numerical Linear System Solving With Parametric Entries By Error Correction. In SNC'14 Proc. 2014 Internat. Workshop on Symbolic-Numeric Comput., Jan Verschelde and Stephen M. Watt (Eds.). Association for Computing Machinery, New York, N. Y., 33--38. http://www.math.ncsu.edu/kaltofen/bibliography/14/BoKa14.pdf.
[3]
Stanley Cabay. 1971. Exact Solution of Linear Equations. In Proceedings of the Second ACM Symposium on Symbolic and Algebraic Manipulation (SYMSAC '71). ACM, New York, NY, USA, 392--398.
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Erich Kaltofen and Clément Pernet. 2013. Cauchy Interpolation with Errors in the Values. Submitted manuscript, 13 pages. (Dec. 2013).
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Erich Kaltofen and Zhengfeng Yang. 2013. Sparse multivariate function recovery from values with noise and outlier errors. In ISSAC 2013 Proc. 38th Internat. Symp. Symbolic Algebraic Comput., Manuel Kauers (Ed.). Association for Computing Machinery, New York, N. Y., 219--226. http://www.math.ncsu.edu/kaltofen/bibliography/13/KaYa13.pdf.
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Erich Kaltofen and Zhengfeng Yang. 2014. Sparse Multivariate Function Recovery With a High Error Rate in Evaluations. In ISSAC 2014 Proc. 39th Internat. Symp. Symbolic Algebraic Comput., Katsusuke Nabeshima (Ed.). Association for Computing Machinery, New York, N. Y., 280--287. http://www.math.ncsu.edu/kaltofen/bibliography/14/KaYa14.pdf.
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Zach Olesh and Arne Storjohann. 2007. The vector rational function reconstruction problems. In Proc. Waterloo Workshop on Computer Algebra: devoted to the 60th birthday of Sergei Abramov (WWCA). 137--149.
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V. Olshevsky and M. Amin Shokrollahi. 2003. A Displacement Approach to Decoding Algebraic Codes. In Algorithms for Structured Matrices: Theory and Applications. American Mathematical Society, Providence, Rhode Island, USA, 265--292. Contemporary Math., vol. 323. URL: http://www.math.uconn.edu/olshevsky/papers/shokrollahi_f.pdf.
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Clément Pernet. 2014. High Performance Algebraic Reliable Computing. Habilitation Thesis. Univ. Joseph Fourier (Grenoble 1).
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Georg Schmidt, Vladimir Sidorenko, and Martin Bossert. 2006. Collaborative Decoding of Interleaved Reed-Solomon Codes and Concatenated Code Designs. CoRR abs/cs/0610074 (2006). http://arxiv.org/abs/cs/0610074
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ISSAC '17: Proceedings of the 2017 ACM International Symposium on Symbolic and Algebraic Computation
July 2017
466 pages
ISBN:9781450350648
DOI:10.1145/3087604
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 23 July 2017

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Author Tags

  1. algebraic error correcting codes
  2. error rate
  3. interleaved codes
  4. rational function recovery

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Cited By

View all
  • (2024)Decoding Simultaneous Rational Evaluation CodesProceedings of the 2024 International Symposium on Symbolic and Algebraic Computation10.1145/3666000.3669686(153-161)Online publication date: 16-Jul-2024
  • (2020)On the uniqueness of simultaneous rational function reconstructionProceedings of the 45th International Symposium on Symbolic and Algebraic Computation10.1145/3373207.3404051(226-233)Online publication date: 20-Jul-2020
  • (2020)On Parametric Linear System SolvingComputer Algebra in Scientific Computing10.1007/978-3-030-60026-6_11(188-205)Online publication date: 14-Sep-2020
  • (2019)LU Factorization with ErrorsProceedings of the 2019 International Symposium on Symbolic and Algebraic Computation10.1145/3326229.3326244(131-138)Online publication date: 8-Jul-2019
  • (2019)Polynomial Linear System Solving with Errors by Simultaneous Polynomial Reconstruction of Interleaved Reed-Solomon Codes2019 IEEE International Symposium on Information Theory (ISIT)10.1109/ISIT.2019.8849582(1542-1546)Online publication date: 7-Jul-2019
  • (2018)What Can (and Can't) we Do with Sparse Polynomials?Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation10.1145/3208976.3209027(25-30)Online publication date: 11-Jul-2018
  • (2018)Error Correction in Fast Matrix Multiplication and InverseProceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation10.1145/3208976.3209001(343-350)Online publication date: 11-Jul-2018

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