Multilayer feedforward neural networks: a canonical form approximation of nonlinearity

DOI10.1080/00207179208934333zbMath0765.93007OpenAlexW2061065535MaRDI QIDQ4020181

A. Julian Morris, Ming. T. Tham, Zhenni Wang

Publication date: 16 January 1993

Published in: International Journal of Control (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207179208934333

zbMATH Keywords

neural networkblack boxmultilayer feedforward neural networks

Mathematics Subject Classification ID

Geometric methods (93B27) Canonical structure (93B10)

Related Items (4)

Techniques for the mathematical analysis of neural networks ⋮ A review of NQR signal processing and analysis techniques ⋮ Performance comparison of neural network models: backpropagationvs. fuzzy artmap ⋮ Neural networks based subgrid scale modeling in large eddy simulations

Cites Work

• Unnamed Item
• Multilayer feedforward networks are universal approximators
• Real and functional analysis
• Approximation by superpositions of a sigmoidal function

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