DocumentCode :
1916356
Title :
Neural networks for odor recognition in artificial noses
Author :
Ludermir, Teresa B. ; Yamazaki, Akio
Author_Institution :
Center of Informatics, Pernambuco Fed. Univ., Recife, Brazil
Volume :
1
fYear :
2003
fDate :
20-24 July 2003
Firstpage :
143
Abstract :
This paper compares the results obtained by different neural network approaches for two odor recognition problems. The data acquisitions were performed by different prototypes of artificial noses. The aim is to provide a comparative analysis of different neural network models, such as multi-layer perceptrons, time delay neural networks and radial basis function networks, for the classification of odors from different substances in artificial noses. Simulated annealing and tabu search were used to optimize neural networks.
Keywords :
chemioception; delays; gas sensors; multilayer perceptrons; radial basis function networks; search problems; simulated annealing; artificial noses; multilayer perceptrons; odor classification; odor recognition; radial basis function networks; simulated annealing; tabu search; time delay neural networks; Artificial neural networks; Data acquisition; Delay effects; Multi-layer neural network; Multilayer perceptrons; Neural networks; Nose; Prototypes; Radial basis function networks; Simulated annealing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2003. Proceedings of the International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-7898-9
Type :
conf
DOI :
10.1109/IJCNN.2003.1223317
Filename :
1223317
Link To Document :
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