NEURAL NETWORK METHOD FOR GALAXY CLASSIFICATION : THE LUMINOSITY FUNCTION OF E/S0 IN CLUSTERS

摘要: Abstract. We present a method based on the non-linear be-haviourofneuralnetworkfortheidentificationoftheearly-typepopulation in cores of galaxy clusters. A Kohonen Self Or-ganising Map applied three-colour photometric catalogueof objects enabled us to select each passband ellipticalgalaxies. measured this way luminosity function ofthe E/S0 galaxies selected way. Such func-tions show peculiarities which disfavour hypothesis itsuniversality often claimed for rich clusters and that can be re-lated past dynamical history cluster as whole.Keywords: galaxies:clusters:general–galaxies:ellipticalandlenticular – galaxies: photome-try methods: miscellaneous1. IntroductionBy now determination (LF) ofgalaxies has reached key point becoming atrue challenge supposed universality its form (as inColless 1989). Different environment density con-ditions are clearly related different morphological mixtures(Dressler 1980; Whitmore & Gilmore 1993) therefore theevidence provided by whole set LF shapes Virgocluster (Binggeli et al. 1988) claims one func-tion all types hardly supported. The clearpresence two distinct classes normal dwarf galaxiesand their evolution leadto search substantial differences from other.Unfortunatelysystematicsurveysspanasmallmagnituderange,going (M