A MULTILAYERED BACKPROPAGATION ARTIFICIAL NEURAL-NETWORK ALGORITHM FOR UV SPECTRAL CLASSIFICATION

In this paper we present an application of an artificial neural networ k model based on a multi-layered backpropagation algorithm for spectra l classification of UV data from the International Ultraviolet Explore r (IUE) low dispersion spectra reference atlas. The model used is simi lar to that of von Hippel et al. (1994), and is found to reduce the cl assification error as compared to the recently reported results on the same data set (Gulati et al. 1994b). The improved version of the netw ork is much simpler in structure and the training time is reduced by a factor of almost 20. Such networks will prove very useful in efficien t classification of large databases.