Universal approximations of continuous fuzzy-valued functions by multi-layer regular fuzzy neural networks

DOI10.1016/S0165-0114(99)00132-3zbMath0976.93055MaRDI QIDQ5931181

Puyin Liu

Publication date: 8 January 2002

Published in: Fuzzy Sets and Systems (Search for Journal in Brave)

zbMATH Keywords

fuzzy-valued functionsfuzzy neural networksuniversal approximator

Mathematics Subject Classification ID

Fuzzy control/observation systems (93C42) Neural networks for/in biological studies, artificial life and related topics (92B20) Approximation by other special function classes (41A30)

Related Items (11)

Approximation of level continuous fuzzy-valued functions by multilayer regular fuzzy neural networks ⋮ Approximation capabilities of multilayer fuzzy neural networks on the set of fuzzy-valued functions ⋮ Universal approximation of polygonal fuzzy neural networks in sense of \(K\)-integral norms ⋮ Approximation of fuzzy-valued functions by regular fuzzy neural networks and the accuracy analysis ⋮ Approximation of fuzzy functions by regular fuzzy neural networks ⋮ A version of the Stone-Weierstrass theorem in fuzzy analysis ⋮ Approximation analysis of feedforward regular fuzzy neural network with two hidden layers ⋮ Fuzzy hyperbolic neural network with time-varying delays ⋮ Incremental learning of dynamic fuzzy neural networks for accurate system modeling ⋮ Approximation of fuzzy neural networks based on Choquet integral ⋮ Regularity of fuzzy measures on complete and separable metric spaces

Cites Work

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• A note on the extension principle for fuzzy sets
• Can neural nets be universal approximators for fuzzy functions?
• Analyses of regular fuzzy neural networks for approximation capabilities
• Can fuzzy neural nets approximate continuous fuzzy functions?

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