Publication result detail

Nonlinear identification based on RBF neural network

BURLAK, V.; PIVOŇKA, P.

Original Title

Nonlinear identification based on RBF neural network

English Title

Nonlinear identification based on RBF neural network

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

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.

English abstract

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.

Keywords

nonlinear identification, RBF neural network, Hammerstein model, ARX model, off-line identification

Key words in English

nonlinear identification, RBF neural network, Hammerstein model, ARX model, off-line identification

Authors

BURLAK, V.; PIVOŇKA, P.

RIV year

2012

Released

23.11.2011

Publisher

DAAAM International Vienna

Location

TU Wien Karlsplatz 13/311 A-1040 Vienna Austria

ISBN

1726-9687

Periodical

DAAAM International Scientific Book

Volume

10

Number

11

State

Republic of Austria

Pages from

547

Pages to

554

Pages count

8

BibTex

@article{BUT74601,
  author="Vladimír {Burlak} and Petr {Pivoňka}",
  title="Nonlinear identification based on RBF neural network",
  journal="DAAAM International Scientific Book",
  year="2011",
  volume="10",
  number="11",
  pages="547--554",
  issn="1726-9687"
}