  An Artificial Neural Network (ANN) has been employed using a supervised
back-propagation scheme to classify 2000 bright sources from the Calgary
database of IRAS (Infrared Astronomy Satellite) spectra in the wavelength
region of 8-23 microns. The data base has been classified into 17
pre-determined classes based on spectral morphology. We have been able to
classify more than 80 percent of the 2000 sources correctly at the first
instance. The speed and robustness of the scheme will allow us to classify the
whole of LRS database, containing more than 50,000 sources in the future.
