1971•Communications of the ACMRequires access

Algorithm 414: Chebyshev approximation of continuous functions by a Chebyshev system of functions

Gene Howard Golub, L. B. Smith

Open publisher page 19 citations

Abstract

The second algorithm of Remez can be used to compute the minimax approximation to a function, ƒ( x ), by a linear combination of functions, { Q i ( x )} n 0 , which form a Chebyshev system. The only restriction on the function to be approximated is that it be continuous on a finite interval [ a , b ]. An Algol 60 procedure is given, which will accomplish the approximation. This implementation of the second algorithm of Remez is quite general in that the continuity of ƒ( x ) is all that is required whereas previous implementations have required differentiability, that the end points of the interval be “critical points,” and that the number of “critical points” be exactly n + 2. Discussion of the method used and of its numerical properties is given as well as some computational examples of the use of the algorithm. The use of orthogonal polynomials (which change at each iteration) as the Chebyshev system is also discussed.

About this research paper

What this paper is about

The second algorithm of Remez can be used to compute the minimax approximation to a function, ƒ( x ), by a linear combination of functions, { Q i ( x )} n 0 , which form a Chebyshev system. The only restriction on the function to be approximated is that it be continuous on a finite interval [ a , b ]. An Algol 60 procedure is given, which will accomplish the approximation. This implementation of the second algorithm of Remez is quite general in that the continuity of ƒ( x ) is all that is required whereas previous implementations have required differentiability, that the end points of the interval be “critical points,” and that the number of “critical points” be exactly n + 2. Discussion of the method used and of its numerical properties is given as well as some computational examples of the use of the algorithm. The use of orthogonal polynomials (which change at each iteration) as the Chebyshev system is also discussed.

Why it matters

OpenAlex reports 19 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The second algorithm of Remez can be used to compute the minimax approximation to a function, ƒ( x ), by a linear combination of functions, { Q i ( x )} n 0 , which form a Chebyshev system. The only restriction on the function to be approximated is that it be continuous on a finite interval [ a , b ]. An Algol 60 procedure is given, which will accomplish the approximation. This implementation of the second algorithm of Remez is quite general in that the continuity of ƒ( x ) is all that is required whereas previous implementations have required differentiability, that the end points of the interval be “critical points,” and that the number of “critical points” be exactly n + 2. Discussion of the method used and of its numerical properties is given as well as some computational examples of the use of the algorithm. The use of orthogonal polynomials (which change at each iteration) as the Chebyshev system is also discussed.

Key concepts: Chebyshev iteration, Mathematics, Minimax approximation algorithm, Chebyshev filter, Equioscillation theorem, Differentiable function, Chebyshev polynomials, Minimax

Related papers

Back to paper searchBrowse research topicsOriginal source
Algorithm 414: Chebyshev approximation of continuous functions by a Chebyshev system of functions — Research Paper | ScholarLens