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"
}