On hermite interpolating L2-approximants

M. A. Bokhari

On hermite interpolating L₂-approximants

M. A. Bokhari^*

^*Corresponding author for this work

King Fahd University of Petroleum & Minerals

Research output: Contribution to journal › Article › peer-review

Abstract

We consider L₂-appoximation of a real-valued square integrable function by polynomials that satisfy certain Hermite interpolation conditions. The solution of the modified minimization problem is found by constructing an orthogonal basis of the underlying approximating subspace. A convergence problem related to the best approximants is considered in a restricted set-up. Some computational aspects based on discretization of the underlying measure are also discussed in detail.

Original language	English
Pages (from-to)	203-216
Number of pages	14
Journal	Dynamic Systems and Applications
Volume	16
Issue number	2
State	Published - Jun 2007

Keywords

Hermite interpolation
Interpolating orthogonal polynomials
Least squares approximation

ASJC Scopus subject areas

General Mathematics

Cite this

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abstract = "We consider L2-appoximation of a real-valued square integrable function by polynomials that satisfy certain Hermite interpolation conditions. The solution of the modified minimization problem is found by constructing an orthogonal basis of the underlying approximating subspace. A convergence problem related to the best approximants is considered in a restricted set-up. Some computational aspects based on discretization of the underlying measure are also discussed in detail.",

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AB - We consider L2-appoximation of a real-valued square integrable function by polynomials that satisfy certain Hermite interpolation conditions. The solution of the modified minimization problem is found by constructing an orthogonal basis of the underlying approximating subspace. A convergence problem related to the best approximants is considered in a restricted set-up. Some computational aspects based on discretization of the underlying measure are also discussed in detail.

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KW - Interpolating orthogonal polynomials

KW - Least squares approximation

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