Multinomial Lagrange-Bernstein approximants
نویسندگان
چکیده
منابع مشابه
Fast multidimensional Bernstein-Lagrange algorithms
In this paper we present two fast algorithms for the Bézier curves and surfaces of an arbitrary dimension. The first algorithm evaluates the Bernstein-Bézier curves and surfaces at a set of specific points by using the fast Bernstein-Lagrange transformation. The second algorithm is an inversion of the first one. Both algorithms reduce the initial problem to computation of some discrete Fourier ...
متن کاملBridging Bernstein and Lagrange polynomials
Linear combinations of iterates of Bernstein polynomials exponentially converging to the Lagrange interpolating polynomial are given. The results are applied in CAGD to get an exponentially fast weighted progressive iterative approximation technique to fit data with finer and finer precision. AMS subject classifications: 41A25, 41A36
متن کاملBernstein Bases are Optimal , but , sometimes , Lagrange Bases are Better
Experimental observations of rootfinding by generalized companion matrix pencils expressed in the Lagrange basis show that the method can sometimes be numerically stable, and indeed sometimes be much more stable than rootfinding of polynomials expressed in even the Bernstein basis. This paper details some of those experiments and provides a theoretical justification for this. We prove that a ne...
متن کاملBasis-Independent Polynomial Division Algorithm Applied to Division in Lagrange and Bernstein Basis
Division algorithms for univariate polynomials represented with respect to Lagrange and Bernstein basis are developed. These algorithms are obtained by abstracting from the classical polynomial division algorithm for polynomials represented with respect to the usual power basis. It is shown that these algorithms are quadratic in the degrees of their inputs, as in the power basis case.
متن کاملPad e-type approximants and errors of Pad e approximants
The Brezinski’s idea of using Pad e-type approximants to estimate errors of Pad e approximants is considerably developed. A new, more e ective method based on this idea is presented and illustrated by numerical examples. c © 1998 Elsevier Science B.V. All rights reserved. AMS classi cation: 41A21
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Signal Processing Letters
سال: 2006
ISSN: 1070-9908
DOI: 10.1109/lsp.2006.871719