Artificial neural networks for quasar selection and photometric redshift determination

Astronomy and Astrophysics

Volumn 523, Issue 1, 2010, Pages

  Yèche, Ch ^a   Petitjean, P ^b   Rich, J ^a   Aubourg, E ^c   Busca, N ^c   Hamilton, J Ch ^c   Le Goff, J M ^a   Paris, I ^b   Peirani, S ^b   Pichon, Ch ^b   Rollinde, E ^b   Vargas Magana M ^c  

^a CEA SACLAY   (France)

^b SORBONNE UNIVERSITÉ   (France)

^c UNIVERSITÉ PARIS DIDEROT   (France)

Author keywords

methods: statistical; quasars: general

Indexed keywords

ABSORPTION SIGNATURE; ACOUSTIC OSCILLATION; ARTIFICIAL NEURAL NETWORK; ARTIFICIAL NEURAL NETWORKS; BARYON OSCILLATIONS; IMAGING DATA; INPUT VARIABLES; LINES-OF-SIGHT; MATTER DENSITY; METHODS:STATISTICAL; MULTI LAYER PERCEPTRON; ORDERS OF MAGNITUDE; OUTPUT VARIABLES; PHOTOMETRIC MEASUREMENTS; QUASARS: GENERAL; RED SHIFT; REDSHIFT DETERMINATION; REDSHIFT RANGE; SLOAN DIGITAL SKY SURVEY; SPECTROSCOPIC SURVEYS; TARGET SELECTION;

ABSORPTION SPECTROSCOPY; MULTILAYER NEURAL NETWORKS; PHOTOMETRY; SURVEYS;

STATISTICAL METHODS;

EID: 78149441870     PISSN: 00046361     EISSN: 14320746     Source Type: Journal    
DOI: 10.1051/0004-6361/200913508     Document Type: Article

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