Equioscillation theorem

In mathematics, the equioscillation theorem concerns the approximation of continuous functions using polynomials when the merit function is the maximum difference (uniform norm). Its discovery is attributed to Chebyshev.^[1]

Statement[edit]

Let ${\displaystyle f}$ be a continuous function from ${\displaystyle [a,b]}$ to ${\displaystyle \mathbb {R} }$. Among all the polynomials of degree ${\displaystyle \leq n}$, the polynomial ${\displaystyle g}$ minimizes the uniform norm of the difference ${\displaystyle \|f-g\|_{\infty }}$ if and only if there are ${\displaystyle n+2}$ points ${\displaystyle a\leq x_{0}<x_{1}<\cdots <x_{n+1}\leq b}$ such that ${\displaystyle f(x_{i})-g(x_{i})=\sigma (-1)^{i}\|f-g\|_{\infty }}$ where ${\displaystyle \sigma }$ is either -1 or +1.^[1][2]

Variants[edit]

The equioscillation theorem is also valid when polynomials are replaced by rational functions: among all rational functions whose numerator has degree ${\displaystyle \leq n}$ and denominator has degree ${\displaystyle \leq m}$, the rational function ${\displaystyle g=p/q}$, with ${\displaystyle p}$ and ${\displaystyle q}$ being relatively prime polynomials of degree ${\displaystyle n-\nu }$ and ${\displaystyle m-\mu }$, minimizes the uniform norm of the difference ${\displaystyle \|f-g\|_{\infty }}$ if and only if there are ${\displaystyle m+n+2-\min\{\mu ,\nu \}}$ points ${\displaystyle a\leq x_{0}<x_{1}<\cdots <x_{n+1}\leq b}$ such that ${\displaystyle f(x_{i})-g(x_{i})=\sigma (-1)^{i}\|f-g\|_{\infty }}$ where ${\displaystyle \sigma }$ is either -1 or +1.^[1]

Algorithms[edit]

Several minimax approximation algorithms are available, the most common being the Remez algorithm.

References[edit]

External links[edit]

• Notes on how to prove Chebyshev’s equioscillation theorem at the Wayback Machine (archived July 2, 2011)
• The Chebyshev Equioscillation Theorem by Robert Mayans
• The de la Vallée-Poussin alternation theorem at the Encyclopedia of Mathematics
• Approximation theory by Remco Bloemen

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