Detail publikace

Nonlinear identification based on RBF neural network

Originální název

Nonlinear identification based on RBF neural network

Anglický název

Nonlinear identification based on RBF neural network

Jazyk

en

Originální abstrakt

This article is focused on the off-line identification of nonlinear dynamic systems. Hammerstein model was used for this identification. RBF (Radial Basis Function) neural network is used here to approximate the input nonlinear static function. This network is implemented as a piecewise linear function.

Anglický abstrakt

This article is focused on the off-line identification of nonlinear dynamic systems. Hammerstein model was used for this identification. RBF (Radial Basis Function) neural network is used here to approximate the input nonlinear static function. This network is implemented as a piecewise linear function.

BibTex


@article{BUT74601,
  author="Vladimír {Burlak} and Petr {Pivoňka}",
  title="Nonlinear identification based on RBF neural network",
  annote="This article is focused on the off-line identification of nonlinear dynamic systems. Hammerstein model was used for this identification. RBF (Radial Basis Function) neural network is used here to approximate the input nonlinear static function. This network is implemented as a piecewise linear function.",
  address="DAAAM International Vienna",
  chapter="74601",
  institution="DAAAM International Vienna",
  number="11",
  volume="10",
  year="2011",
  month="november",
  pages="547--554",
  publisher="DAAAM International Vienna",
  type="journal article - other"
}