Hybrid neural systems for pattern recognition in artificial noses.
This work examines the use of Hybrid Intelligent Systems in the pattern recognition system of an artificial nose. The connectionist approaches Multi-Layer Perceptron and Time Delay Neural Networks, and the hybrid approaches Feature-Weighted Detector and Evolving Neural Fuzzy Networks were investigated. A Wavelet Filter is evaluated as a preprocessing method for odor signals. The signals generated by an artificial nose were composed by an array of conducting polymer sensors and exposed to two different odor databases.
Zanchettin
Cleber
C
CIn - Federal University of Pernambuco, Cidade Universitaria, Recife - PE, P. O. Box 7851, 50.732-970, Brazil. cz@cin.ufpe.br
Ludermir
Teresa B
TB
D000818:Animals; D001187:Artificial Organs; D017143:Fuzzy Logic; D006801:Humans; D016571:Neural Networks, Computer; D009666:Nose; D010363:Pattern Recognition, Automated / Q000379:methods*; D025341:Principal Component Analysis; D012903:Smell / Q000502:physiology*