Universal Approximation Using Radial-Basis-Function Networks

@article{Park1991UniversalAU,
  title={Universal Approximation Using Radial-Basis-Function Networks},
  author={Jooyoung Park and Irwin W. Sandberg},
  journal={Neural Computation},
  year={1991},
  volume={3},
  pages={246-257}
}
There have been several recent studies concerning feedforward networks and the problem of approximating arbitrary functionals of a finite number of real variables. Some of these studies deal with cases in which the hidden-layer nonlinearity is not a sigmoid. This was motivated by successful applications of feedforward networks with nonsigmoidal hidden-layer units. This paper reports on a related study of radial-basis-function (RBF) networks, and it is proved that RBF networks having one hidden… 
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