Pregled bibliografske jedinice broj: 108841
Comparison of the Lagrange Constrained Neural Network with Traditional ICA methods
Comparison of the Lagrange Constrained Neural Network with Traditional ICA methods // Proceedings of the World Congress Computational Inteligence - Volume I
Piscataway (NJ): Institute of Electrical and Electronics Engineers (IEEE), 2002. str. 466-471 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 108841 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Comparison of the Lagrange Constrained Neural Network with Traditional ICA methods
Autori
Szu, Harold ; Kopriva, Ivica ;
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the World Congress Computational Inteligence - Volume I
/ - Piscataway (NJ) : Institute of Electrical and Electronics Engineers (IEEE), 2002, 466-471
Skup
The 2002 IEEE World Congress on Computational Intelligence
Mjesto i datum
Honolulu (HI), Sjedinjene Američke Države, 12.05.2002. - 17.05.2002
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
indepemdet component analysis; Lagrange constrained neural network
Sažetak
The paper presents comparison between the a priori MaxEnt and the a posteriori MaxEnt methodologies, namely Lagrange Constraint Neural Network (LCNN) by Szu in 1997 and ICA algorithms by Bell-Sejnowski-Amari-Oja (BSAO) and many others since 1996. We chose the remote sensing application because it is the only real world application that we know to be truly linear, single path, and instantaneous mixing of the unknown ground spectral objects.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
036024
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Ivica Kopriva
(autor)
