On the Partitioning Capabilities of Feedforward Neural Networks with Sigmoid Nodes

DOI10.1162/089976603322362437zbMath1085.68632OpenAlexW2152966207WikidataQ35544475 ScholiaQ35544475MaRDI QIDQ4461331

Konstantinos Koutroumbas

Publication date: 30 March 2004

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

Full work available at URL: https://doi.org/10.1162/089976603322362437

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Computational Properties of Networks of Synchronous Groups of Spiking Neurons

Cites Work

• Unnamed Item
• Multilayer feedforward networks are universal approximators
• Approximation by superpositions of a sigmoidal function
• Gaussian radial basis functions and inner product spaces.

This page was built for publication: On the Partitioning Capabilities of Feedforward Neural Networks with Sigmoid Nodes