articleTop 1% cited
Approximation and Radial-Basis-Function Networks
Neural Computation · 1993 · Vol. 5(2) · pp. 305–316
Jooyoung Park✉(The University of Texas at Austin)Irwin W. Sandberg(The University of Texas at Austin)
Abstract
This paper concerns conditions for the approximation of functions in certain general spaces using radial-basis-function networks. It has been shown in recent papers that certain classes of radial-basis-function networks are broad enough for universal approximation. In this paper these results are considerably extended and sharpened.
Neural Networks and ApplicationsFuzzy Logic and Control SystemsNumerical Methods and AlgorithmsRadial basis functionRadial basis function networkBasis (linear algebra)Function (biology)Function approximationBasis functionMathematicsApplied mathematicsComputer scienceArtificial neural network
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817
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18.00
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References
Approximation capabilities of multilayer feedforward networks
Neural Networks · 1991 · 5,992 citations
Universal Approximation Using Radial-Basis-Function Networks
Neural Computation · 1991 · 4,027 citations
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