A universal mapping for Kolmogorov's superposition theorem

DOI10.1016/S0893-6080(09)80020-8zbMath0788.26010OpenAlexW2071828141MaRDI QIDQ1317543

David A. Sprecher

Publication date: 24 May 1994

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0893-6080(09)80020-8

zbMATH Keywords

uniform continuityKolmogorovHecht-Nielsen three-layer feedforward neural networkprocessing elementssuperposition of continuous functions

Mathematics Subject Classification ID

Neural networks for/in biological studies, artificial life and related topics (92B20) Representation and superposition of functions (26B40)

Related Items (4)

Computational aspects of Kolmogorov's superposition theorem ⋮ Stretchy binary classification ⋮ A note on computing with Kolmogorov superpositions without iterations ⋮ A three layer neural network can represent any multivariate function

Cites Work

• On the representation of continuous functions of many variables by superposition of continuous functions of one variable and addition
• On the Structure of Continuous Functions of Several Variables

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