Publication detail

Global versus local aproximation in inverse problem

KREJSA, J. VĚCHET, S. PULCHART, J.

Czech title

Globální versus lokální aproximátory použité pro řešení inverzní úlohy.

English title

Global versus local aproximation in inverse problem

Type

journal article - other

Language

en

Original abstract

The paper compares global and local approximation methods used in inverse problems. Global approximators are represented by feedforward multilayer neural network (FFNN); local approximators are represented by Locally Weighted Regression (LWR) and Receptive Field Weighted Regression (RFWR).

Czech abstract

Článek porovnává globální a lokální aproximační metody použité pro řešení inverzní úlohy. Globální aproximátory zastupuje vícevrstvá dopředná umělá neuronová síť; lokální aproximátory zastupují metody lokálně vážené regrese (LWR) a vážené regrese recepčních polí (RFWR).

English abstract

The paper compares global and local approximation methods used in inverse problems. Global approximators are represented by feedforward multilayer neural network (FFNN); local approximators are represented by Locally Weighted Regression (LWR) and Receptive Field Weighted Regression (RFWR).

Keywords in English

inverse problem, approximators, neural networks, weighted regression

RIV year

2004

Released

23.09.2004

Publisher

Warsaw University of Technology, Faculty of Mechatronics

Location

Warsaw, Poland

ISSN

0033-2089

Journal

Elektronika

Volume

2004

Number

8-9

Pages count

4

BIBTEX


@article{BUT45414,
  author="Jiří {Krejsa} and Stanislav {Věchet} and Jaroslav {Pulchart},
  title="Global versus local aproximation in inverse problem",
  journal="Elektronika",
  year="2004",
  volume="2004",
  number="8-9",
  month="September",
  publisher="Warsaw University of Technology, Faculty of Mechatronics",
  address="Warsaw, Poland",
  issn="0033-2089"
}