By Topic

HNS-a hybrid neural system and its use for the classification of stars

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
M. Klusch ; Inst. fur Inf. und Praktische Math., Kiel Univ., Germany

A novel hybrid neural approach for a fully automated spectral and luminosity classification of stars is presented. The hybrid neural system (HNS) integrates a neural classifier and a semantic network used for similarity based reasoning and conceptual knowledge representation, respectively. In the paper, the structure, functionality and application of the hybrid system are presented. The demonstrated functional capabilities, performance and results of stellar classification of the HNS show significant improvements compared to conventional astronomical techniques. After knowledge acquisition is once completed, the system classifies stellar objects very fast, reliable and without any need for pre-classification of them. In particular, the HNS is also able to compare classes of stars without forcing the user to give any raw input data and special knowledge about relations between these classes. Moreover, this new hybrid approach offers a variety of applications in other areas.

Published in:

Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on  (Volume:1 )

Date of Conference:

25-29 Oct. 1993