Self-organized network with a supervised training and its comparison with FALVQ in artificial odor recognition system

Research output: Contribution to journalConference article

3 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)85-90
Number of pages6
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4036
Publication statusPublished - 1 Jan 2000
EventChemical and Biological Sensing - Orlando, FL, USA
Duration: 24 Apr 200025 Apr 2000

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