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Proceedings Paper

Self-organized network with a supervised training and its comparison with FALVQ in artificial odor recognition system
Author(s): Benyamin Kusumoputro; Linda Rostiviani; Ari Saptawijaya
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Paper Abstract

Artificial odor recognition system is developed in order to mimic the human sensory test in cosmetics, parfum and beverage industries. The developed system however, lacks of ability to recognize the unknown type of odor. To improve the system's capability, a hybrid neural system with a supervised learning paradigm is developed and used as a pattern classifier. In this paper, the performance of the hybrid neural system is investigated, together with that of FALVQ neural system.

Paper Details

Date Published: 28 July 2000
PDF: 6 pages
Proc. SPIE 4036, Chemical and Biological Sensing, (28 July 2000); doi: 10.1117/12.394070
Show Author Affiliations
Benyamin Kusumoputro, Univ. of Indonesia (Indonesia)
Linda Rostiviani, Univ. of Indonesia (Indonesia)
Ari Saptawijaya, Univ. of Indonesia (Indonesia)

Published in SPIE Proceedings Vol. 4036:
Chemical and Biological Sensing
Patrick J. Gardner, Editor(s)

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