609 research outputs found
On the constrained mock-Chebyshev least-squares
The algebraic polynomial interpolation on uniformly distributed nodes is
affected by the Runge phenomenon, also when the function to be interpolated is
analytic. Among all techniques that have been proposed to defeat this
phenomenon, there is the mock-Chebyshev interpolation which is an interpolation
made on a subset of the given nodes whose elements mimic as well as possible
the Chebyshev-Lobatto points. In this work we use the simultaneous
approximation theory to combine the previous technique with a polynomial
regression in order to increase the accuracy of the approximation of a given
analytic function. We give indications on how to select the degree of the
simultaneous regression in order to obtain polynomial approximant good in the
uniform norm and provide a sufficient condition to improve, in that norm, the
accuracy of the mock-Chebyshev interpolation with a simultaneous regression.
Numerical results are provided.Comment: 17 pages, 9 figure
Chebfun and numerical quadrature
Chebfun is a Matlab-based software system that overloads Matlab’s discrete operations for vectors and matrices to analogous continuous operations for functions and operators. We begin by describing Chebfun’s fast capabilities for Clenshaw–Curtis and also Gauss–Legendre, –Jacobi, –Hermite, and –Laguerre quadrature, based on algorithms of Waldvogel and Glaser, Liu, and Rokhlin. Then we consider how such methods can be applied to quadrature problems including 2D integrals over rectangles, fractional derivatives and integrals, functions defined on unbounded intervals, and the fast computation of weights for barycentric interpolation
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