title: Hybrid neural systems for pattern recognition in artificial noses.
abstract: 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.
authors.affiliation: CIn - Federal University of Pernambuco, Cidade Universitaria, Recife - PE, P. O. Box 7851, 50.732-970, Brazil. cz@cin.ufpe.br
authors.forename: Cleber
authors.initials: C
authors.lastname: Zanchettin
authors.forename: Teresa B
authors.initials: TB
authors.lastname: Ludermir
mesh_terms: 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*