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Adding local short description: "Type of artificial neural network that uses radial basis functions as activation functions", overriding Wikidata description "an artificial neural network that uses radial basis functions as activation functions" (Shortdesc helper) |
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{{short description|Type of artificial neural network that uses radial basis functions as activation functions}}
In the field of [[mathematical modeling]], a '''radial basis function network''' is an [[artificial neural network]] that uses [[radial basis function]]s as [[activation function]]s. The output of the network is a [[linear combination]] of radial basis functions of the inputs and neuron parameters. Radial basis function networks have many uses, including [[function approximation]], [[time series prediction]], [[Statistical classification|classification]], and system [[Control theory|control]]. They were first formulated in a 1988 paper by Broomhead and Lowe, both researchers at the [[Royal Signals and Radar Establishment]].<ref>{{cite techreport
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