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.
- 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. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- Erich Kaltofen and Clément Pernet. 2013. Cauchy Interpolation with Errors in the Values. Submitted manuscript, 13 pages. (Dec. 2013).Google Scholar
- 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. Google ScholarDigital Library
- 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. Google ScholarDigital Library
- M. T. McClellan. 1973. The exact solution of systems of linear equations with polynomial coefficients. J. ACM 20 (1973), 563--588. Google ScholarDigital Library
- 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.Google ScholarCross Ref
- 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. Google ScholarDigital Library
- Clément Pernet. 2014. High Performance Algebraic Reliable Computing. Habilitation Thesis. Univ. Joseph Fourier (Grenoble 1).Google Scholar
- 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/0610074Google Scholar
- L. R. Welch and E. R. Berlekamp. 1986. Error Correction of Algebraic Block Codes. US Patent 4,633470. (1986). See http://patft.uspto.gov/.Google Scholar
Index Terms
- Early Termination in Parametric Linear System Solving and Rational Function Vector Recovery with Error Correction
Recommendations
Sparse multivariate function recovery with a high error rate in the evaluations
ISSAC '14: Proceedings of the 39th International Symposium on Symbolic and Algebraic ComputationIn [Kaltofen and Yang, Proc. ISSAC 2013] we have generalized algebraic error-correcting decoding to multivariate sparse rational function interpolation from evaluations that can be numerically inaccurate and where several evaluations can have severe ...
Asymptotic Error Estimates for L2 Best Rational Approximants to Markov Functions
Let f(z)=@!(t-z)^-^1d@m(t) be a Markov function, where @m is a positive measure with compact support in R. We assume that supp(@m)@?(-1, 1), and investigate the best rational approximants to f in the Hardy space H^0"2(V), where V@?{z@?C||z|>1} and H^0"2(...
Supersparse black box rational function interpolation
ISSAC '11: Proceedings of the 36th international symposium on Symbolic and algebraic computationWe present a method for interpolating a supersparse blackbox rational function with rational coefficients, for example, a ratio of binomials or trinomials with very high degree. We input a blackbox rational function, as well as an upper bound on the ...
Comments