TY - JOUR
T1 - Self-organized network with a supervised training and its comparison with FALVQ in artificial odor recognition system
AU - Putro, Benyamin Kusumo
AU - Rostiviani, Linda
AU - Saptawijaya, Ari
PY - 2000
Y1 - 2000
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=0033697165&partnerID=8YFLogxK
U2 - 10.1117/12.394070
DO - 10.1117/12.394070
M3 - Conference article
AN - SCOPUS:0033697165
SN - 0277-786X
VL - 4036
SP - 85
EP - 90
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
T2 - Chemical and Biological Sensing
Y2 - 24 April 2000 through 25 April 2000
ER -