Can neural nets be universal approximators for fuzzy functions?

DOI10.1016/S0165-0114(97)00069-9zbMath0935.68088MaRDI QIDQ1302234

Buckley, James J., Hayashi, Yoichi

Publication date: 16 November 1999

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

zbMATH Keywords

neural netsfuzzy functions

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items

Universal approximation of polygonal fuzzy neural networks in sense of \(K\)-integral norms ⋮ Universal approximations of continuous fuzzy-valued functions by multi-layer regular fuzzy neural networks ⋮ Universal approximators for fuzzy functions ⋮ Stability analysis of neural net controllers using fuzzy neural networks ⋮ Analysis of approximation of continuous fuzzy functions by multivariate fuzzy polynomials

Cites Work

• On using \(\alpha\)-cuts to evaluate fuzzy equations
• Differentials of fuzzy functions
• Derived eigenvalues of symmetric matrices, with applications to distance geometry
• Solving fuzzy equations using neural nets
• Neural net solutions to fuzzy problems: The quadratic equation
• Neural net solutions to fuzzy linear programming
• Genetic algorithms and soft computing
• Can fuzzy neural nets approximate continuous fuzzy functions?
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