Knowledge extraction using artificial neural networks: application to radar target identification
Identifieur interne : 000883 ( PascalFrancis/Corpus ); précédent : 000882; suivant : 000884Knowledge extraction using artificial neural networks: application to radar target identification
Auteurs : J.-F. Remm ; F. AlexandreSource :
- Signal processing [ 0165-1684 ] ; 2002.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
Artificial neural networks are efficient for performing signal processing but are not able to explain their decision nor to extract knowledge from data. We propose here a way to extract rules and hints from the hidden layers of a multilayered perceptron. The network is first pruned and then the progressive use of a simpler transfer function can allow such knowledge extraction. This method has been successfully applied to radar signal identification.
Notice en format standard (ISO 2709)
Pour connaître la documentation sur le format Inist Standard.
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Format Inist (serveur)
NO : | PASCAL 02-0200588 INIST |
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ET : | Knowledge extraction using artificial neural networks: application to radar target identification |
AU : | REMM (J.-F.); ALEXANDRE (F.) |
AF : | LORIA-INRIA, BP 239/54506 Vandœuvre/France (1 aut., 2 aut.) |
DT : | Publication en série; Courte communication, note brève; Niveau analytique |
SO : | Signal processing; ISSN 0165-1684; Coden SPRODR; Pays-Bas; Da. 2002; Vol. 82; No. 1; Pp. 117-120; Bibl. 8 ref. |
LA : | Anglais |
EA : | Artificial neural networks are efficient for performing signal processing but are not able to explain their decision nor to extract knowledge from data. We propose here a way to extract rules and hints from the hidden layers of a multilayered perceptron. The network is first pruned and then the progressive use of a simpler transfer function can allow such knowledge extraction. This method has been successfully applied to radar signal identification. |
CC : | 001D02C06; 001D04B05; 001D04A05C |
FD : | Réseau neuronal; Extraction caractéristique; Détection cible; Radar; Perceptron multicouche; Traitement signal |
ED : | Neural network; Feature extraction; Target detection; Radar; Multilayer perceptrons; Signal processing |
SD : | Red neuronal; Detección blanco; Radar; Procesamiento señal |
LO : | INIST-18015.354000102253900080 |
ID : | 02-0200588 |
Links to Exploration step
Pascal:02-0200588Le document en format XML
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<front><div type="abstract" xml:lang="en">Artificial neural networks are efficient for performing signal processing but are not able to explain their decision nor to extract knowledge from data. We propose here a way to extract rules and hints from the hidden layers of a multilayered perceptron. The network is first pruned and then the progressive use of a simpler transfer function can allow such knowledge extraction. This method has been successfully applied to radar signal identification.</div>
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