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We approximate the d complex zeros of a univariate polynomial p(x) of a degree d or those zeros that lie in a fixed region of interest on the complex plane such as a disc or a square. Our divide and conquer algorithm of STOC 1995 supports…

Symbolic Computation · Computer Science 2023-06-13 Victor Y. Pan , Soo Go , Qi Luan , Liang Zhao

We present a new method for approximating real-valued functions on ${\mathbb R}^+$ by linear combinations of exponential functions with complex coefficients. The approach is based on a multi-point Pad\'e approximation of the Laplace…

Numerical Analysis · Mathematics 2026-05-05 Alexey Kuznetsov , Armin Mohammadioroojeh

In this article, a formulation of a point-collocation method in which the unknown function is approximated using global expansion in tensor product Bernstein polynomial basis is presented. Bernstein polynomials used in this study are…

Numerical Analysis · Mathematics 2012-11-16 Nikola Mirkov , Bosko Rasuo

Let $p(x)=a_0 + a_1 x + \ldots + a_n x^n$ be a polynomial with all roots real and satisfying $x \leq -\delta$ for some $0<\delta <1$. We show that for any $0 < \epsilon <1$, the value of $p(1)$ is determined within relative error $\epsilon$…

Combinatorics · Mathematics 2018-06-21 Alexander Barvinok

Dual Bernstein polynomials of one or two variables have proved to be very useful in obtaining B\'{e}zier form of the $L^2$-solution of the problem of best polynomial approximation of B\'{e}zier curve or surface. In this connection, the…

Numerical Analysis · Mathematics 2016-10-21 Stanisław Lewanowicz , Paweł Keller , Paweł Woźny

Computing the roots of a univariate polynomial is a fundamental and long-studied problem of computational algebra with applications in mathematics, engineering, computer science, and the natural sciences. For isolating as well as for…

Symbolic Computation · Computer Science 2015-03-12 Michael Sagraloff , Kurt Mehlhorn

Approximate computing has shown to provide new ways to improve performance and power consumption of error-resilient applications. While many of these applications can be found in image processing, data classification or machine learning, we…

Numerical Analysis · Computer Science 2017-03-08 Michael Lass , Thomas D. Kühne , Christian Plessl

We propose a generalization of the Weierstrass iteration for over-constrained systems of equations and we prove that the proposed method is the Gauss-Newton iteration to find the nearest system which has at least $k$ common roots and which…

Symbolic Computation · Computer Science 2014-01-22 Olivier Ruatta , Mark Sciabica , Agnes Szanto

We present a simple randomized polynomial time algorithm to approximate the mixed discriminant of $n$ positive semidefinite $n \times n$ matrices within a factor $2^{O(n)}$. Consequently, the algorithm allows us to approximate in randomized…

Rings and Algebras · Mathematics 2008-02-03 Alexander Barvinok

We state a kind of Euclidian division theorem: given a polynomial P(x) and a divisor d of the degree of P, there exist polynomials h(x),Q(x),R(x) such that P(x) = h(Q(x)) +R(x), with deg h=d. Under some conditions h,Q,R are unique, and Q is…

Algebraic Geometry · Mathematics 2009-10-12 Arnaud Bodin

We propose an algorithm that approximates a given matrix polynomial of degree $d$ by another skew-symmetric matrix polynomial of a specified rank and degree at most $d$. The algorithm is built on recent advances in the theory of generic…

Numerical Analysis · Mathematics 2026-01-26 Andrii Dmytryshyn , Froilán M. Dopico , Rakel Hellberg

Univariate polynomial root-finding is both classical and important for modern computing. Frequently one seeks just the real roots of a polynomial with real coefficients. They can be approximated at a low computational cost if the polynomial…

Numerical Analysis · Mathematics 2014-07-01 Victor Y. Pan

This paper presents a method to determine a set of basis polynomials from the extended Euclidean algorithm that allows Generalized Minimum Distance decoding of Reed-Solomon codes with a complexity of O(nd).

Information Theory · Computer Science 2010-09-08 Sabine Kampf , Martin Bossert

The inverse of a large matrix can often be accurately approximated by a polynomial of degree significantly lower than the order of the matrix. The iteration polynomial generated by a run of the GMRES algorithm is a good candidate, and its…

Numerical Analysis · Mathematics 2025-02-26 Mark Embree , Joel A. Henningsen , Jordan Jackson , Ronald B. Morgan

We consider the problem of finding for a given $N$-tuple of polynomials (real or complex) the closest $N$-tuple that has a common divisor of degree at least $d$. Extended weighted Euclidean seminorm of the coefficients is used as a measure…

Optimization and Control · Mathematics 2015-11-05 Konstantin Usevich , Ivan Markovsky

In this article, we describe an implementation of a polynomial system solver to compute the approximate solutions of a 0-dimensional polynomial system with finite precision p-adic arithmetic. We also describe an improvement to an algorithm…

Numerical Analysis · Mathematics 2019-07-09 Avinash Kulkarni

We describe a new incomplete but terminating method for real root finding for large multivariate polynomials. We take an abstract view of the polynomial as the set of exponent vectors associated with sign information on the coefficients.…

Symbolic Computation · Computer Science 2018-04-30 Thomas Sturm

An algorithm based on the Ehrlich-Aberth root-finding method is presented for the computation of the eigenvalues of a T-palindromic matrix polynomial. A structured linearization of the polynomial represented in the Dickson basis is…

Numerical Analysis · Mathematics 2011-11-15 Luca Gemignani , Vanni Noferini

Univariate polynomial root-finding has been studied for four millennia and very intensively in the last decades. Our new near-optimal root-finders approximate all zeros of a polynomial p almost as fast as one accesses its coefficients with…

Numerical Analysis · Computer Science 2024-07-02 Victor Y. Pan

We propose and investigate two new methods to approximate $f({\bf A}){\bf b}$ for large, sparse, Hermitian matrices ${\bf A}$. The main idea behind both methods is to first estimate the spectral density of ${\bf A}$, and then find…

Numerical Analysis · Computer Science 2018-08-30 Li Fan , David I Shuman , Shashanka Ubaru , Yousef Saad