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A novel threshold optimization of ML-CFAR detector in Weibull clutter using fuzzy-neural networks

Author
MEZACHE, Amar1 ; SOLTANI, Faouzi1
[1] Département d'Electronique, Faculté des Sciences de l'Ingénieur. Université de Constantine, Route d'Ain El Bey, Constantine 25000, Algeria
Source

Signal processing. 2007, Vol 87, Num 9, pp 2100-2110, 11 p ; ref : 13 ref

CODEN
SPRODR
ISSN
0165-1684
Scientific domain
Telecommunications
Publisher
Elsevier Science, Amsterdam
Publication country
Netherlands
Document type
Article
Language
English
Author keyword
CFAR Fuzzy-neural networks Genetic algorithms Weibull clutter
Keyword (fr)
Algorithme apprentissage Algorithme génétique Apprentissage Détection optimale Evaluation performance Fouillis écho Loi Weibull Maximum vraisemblance Optimisation Réseau neuronal flou Système flou Taux fausse alarme
Keyword (en)
Learning algorithm Genetic algorithm Learning Optimal detection Performance evaluation Clutter Weibull distribution Maximum likelihood Optimization Fuzzy neural nets Fuzzy system False alarm rate
Keyword (es)
Algoritmo aprendizaje Algoritmo genético Aprendizaje Detección optimal Evaluación prestación Confusión eco Ley Weibull Maxima verosimilitud Optimización Sistema difuso Porcentaje falsa alarma
Classification
Pascal
001 Exact sciences and technology / 001D Applied sciences / 001D02 Computer science; control theory; systems / 001D02C Artificial intelligence / 001D02C06 Connectionism. Neural networks

Discipline
Computer science : theoretical automation and systems
Origin
Inist-CNRS
Database
PASCAL
INIST identifier
20085475

Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS

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