Radial basis function network: Difference between revisions

Revision as of 19:47, 23 August 2007

Revision as of 08:56, 10 October 2007

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A '''radial basis function network''' is an [[artificial neural network]] which uses [[radial basis function]]s as activation functions. They are used in [[function approximation]], [[time series prediction]], and [[Control theory|control]].

==Network an architecture==

[[Image:060804 architecture.png|thumb|350px|right|Figure 1: Architecture of a radial basis function network. An input vector '''x''' is used as input to all radial basis functions, each with different parameters. The output of the network is a linear combination of the outputs from radial basis functions.]]