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Approximation Theory and Its Applications
Article . 1993 . Peer-reviewed
License: Springer Nature TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
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Degree of approximation by superpositions of a sigmoidal function

Authors: Chen, Debao;

Degree of approximation by superpositions of a sigmoidal function

Abstract

Summary: We study the degree of approximation by superpositions of a sigmoidal function. We mainly consider the univariate case. If \(f\) is a continuous function, we prove that for any bounded sigmoidal function \(\sigma\), \(d_{n,\sigma}(f)\leq \|\sigma\| \omega \bigl( f,{1\over{n+1}}\bigr)\). For the Heaviside function \(H(x)\), we prove that \(d_{n,H}(f)\leq \omega \bigl( f, {1\over {2n+1)}} \bigr)\). If \(f\) is a continuous function of bounded variation, we prove that \(d_{n,\sigma} (f)\leq {{\|\sigma\|} \over {n+1}} V(f)\) and \(d_{n,H}\leq {1\over {2n+1}} V(f)\). For the Heaviside function, the coefficient 1 and the approximation orders are the best possible. We compare these results with the classical Jackson and Bernstein theorems, and make some conjectures for further study.

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Keywords

sigmoidal function, Rate of convergence, degree of approximation, Approximation by other special function classes, Heaviside function

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
49
Top 10%
Top 10%
Average
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