New study on neural networks: the essential order of approximation
type: Item
instance of: scholarly article
title: New study on neural networks: the essential order of approximation
zbMATH Open document ID: 1398.65023
published in: Neural Networks
publication date: 2018-09-27T00:00:00Z
Mathematics Subject Classification ID: 65D15
zbMATH DE Number: 6944398
zbMATH Keywords: essential order of approximation
zbMATH Keywords: nearly exponential type neural networks
zbMATH Keywords: modulus of smoothness
Wikidata QID: Q51723412
author: Jianjun Wang
author: Zongben Xu
MaRDI profile type: Publication
full work available at URL: j.neunet.2010.01.004
OpenAlex ID: W2097698789
cites work: Universal approximation bounds for superpositions of a sigmoidal function
cites work: Approximation by Ridge functions and neural networks with one hidden layer
cites work: Approximation by superpositions of a sigmoidal function
cites work: Q3817079
cites work: Q4067513
cites work: Multilayer feedforward networks are universal approximators
cites work: Q4118037
cites work: Approximation by superposition of sigmoidal and radial basis functions
cites work: Dimension-independent bounds on the degree of approximation by neural networks
cites work: Degree of approximation by neural and translation networks with a single hidden layer
cites work: Q4064526
cites work: Efficient estimation of neural weights by polynomial approximation
cites work: The essential order of approximation for neural networks
cites work: The essential order of approximation for nearly exponential type neural networks
DOI: 10.1016/J.NEUNET.2010.01.004
description: scientific article; zbMATH DE number 6944398