The errors of approximation for feedforward neural networks in thelpmetric

DOI10.1016/j.mcm.2008.07.031zbMath1165.41312OpenAlexW2027897038MaRDI QIDQ2390185

Rui Zhang, Feilong Cao

Publication date: 21 July 2009

Published in: Mathematical and Computer Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.mcm.2008.07.031

zbMATH Keywords

neural networksapproximationestimate of error\(Lp\) metric

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Neural nets applied to problems in time-dependent statistical mechanics (82C32) Approximation by other special function classes (41A30)

Related Items (4)

Generalized extreme learning machine acting on a metric space ⋮ Convergence for a family of neural network operators in Orlicz spaces ⋮ Estimates for the neural network operators of the max-product type with continuous and \(p\)-integrable functions ⋮ Quantitative estimates involving K-functionals for neural network-type operators

Cites Work

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• Constructive approximate interpolation by neural networks
• The essential order of approximation for neural networks
• Approximation by Ridge functions and neural networks with one hidden layer
• Uniform approximation by neural networks
• Multilayer feedforward networks are universal approximators
• Degree of approximation by neural and translation networks with a single hidden layer
• Superconvergence of Projection Methods for Weakly Singular Integral Operators
• Universal approximation bounds for superpositions of a sigmoidal function
• Advances in Neural Networks – ISNN 2005
• Approximation by superpositions of a sigmoidal function

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