Báo cáo hóa học: " Astrophysical Information from Objective Prism Digitized Images: Classification with an Artificial Neural Network Emmanuel Bratsolis"

Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Astrophysical Information from Objective Prism Digitized Images: Classification with an Artificial Neural Network Emmanuel Bratsolis | EURASIP Journal on Applied Signal Processing 2005 15 2536-2545 2005 Hindawi Publishing Corporation Astrophysical Information from Objective Prism Digitized Images Classification with an Artificial Neural Network Emmanuel Bratsolis Departement Traitement du Signal et des Images Ecole Nationale Supérieure des Telecommunications 46 rue Barrault 75013 Paris France Email bratsoli@ Section of Astrophysics Astronomy and Mechanics Department of Physics University of Athens 15784 Athens Greece Email ebrats@ Received 28 May 2004 Revised 14 December 2004 Stellar spectral classification is not only a tool for labeling individual stars but is also useful in studies of stellar population synthesis. Extracting the physical quantities from the digitized spectral plates involves three main stages detection extraction and classification of spectra. Low-dispersion objective prism images have been used and automated methods have been developed. The detection and extraction problems have been presented in previous works. In this paper we present a classification method based on an artificial neural network ANN . We make a brief presentation of the entire automated system and we compare the new classification method with the previously used method of maximum correlation coefficient MCC . Digitized photographic material has been used here. The method can also be used on CCD spectral images. Keywords and phrases objective prism stellar spectra classification artificial neural network. 1. INTRODUCTION Large surveys are concerned with two things. The first is finding unusual objects. Once detected these unusual objects must always be analyzed individually. The second one is to do statistics with large numbers of objects. In this case we need an automated classification system. High-quality film copies of IIIa-J broad blue-green band plates taken with the m UK Schmidt Telescope in Australia have been used. The spectral plates are with dispersion of 2 440 A mm at HY .

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