DocumentCode :
2647501
Title :
An artificial olfactory system using tiered artificial neural networks
Author :
Saunders, Bruce W. ; Thiel, David V. ; Mackay-sim, Alan
Author_Institution :
Griffith Univ., Brisbane, Qld., Australia
fYear :
1994
fDate :
29 Nov-2 Dec 1994
Firstpage :
76
Lastpage :
80
Abstract :
A method for implementing an electronic nose, trained to discriminate between different odorants is demonstrated. The `nose´ consists of a number of chemically modified gas sensors. On exposure to odorants, a unique dynamic response pattern (termed “kinetic signature”) is obtained for each sensor, based on the interfacial kinetics of the odorant and sensor coating. These kinetic signatures are used to train a multi-tiered artificial neural network (ANN) to discriminate between different odorants. Subsequent recognition of odorants presented to the `nose´ is by means of identifying two dimensional olfactory response maps, generated from the outputs of the ANN
Keywords :
chemioception; dynamic response; gas sensors; intelligent sensors; neural nets; 2D olfactory response maps; artificial olfactory system; chemically modified gas sensors; dynamic response pattern; electronic nose; interfacial kinetics; kinetic signature; odorant discrimination training; odorant recognition; outputs; sensor coating; tiered artificial neural networks; Artificial neural networks; Chemical sensors; Coatings; Crystals; Electronic noses; Frequency response; Kinetic theory; Olfactory; Sensor arrays; Sensor systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Systems,1994. Proceedings of the 1994 Second Australian and New Zealand Conference on
Conference_Location :
Brisbane, Qld.
Print_ISBN :
0-7803-2404-8
Type :
conf
DOI :
10.1109/ANZIIS.1994.396946
Filename :
396946
Link To Document :
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