@article{
 title = {Hybrid neural systems for pattern recognition in artificial noses},
 type = {article},
 year = {2005},
 keywords = {Artificial nose,Evolving fuzzy neural networks,Hybrid neural systems,Multi-layer perceptron,Time delay neural networks,Wavelet filter},
 volume = {15},
 id = {fcafda8e-da99-3a51-907f-08e4af37367c},
 created = {2019-02-14T18:02:00.205Z},
 file_attached = {false},
 profile_id = {74e7d4ea-3dac-3118-aab9-511a5b337e8f},
 last_modified = {2019-02-14T18:02:00.205Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 abstract = {This work examines the use of Hybrid Intelligent Systems in the pattern recognition system of an artificial nose. The connectionist approaches Multi-Layer Perception 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. © World Scientific Publishing Company.},
 bibtype = {article},
 author = {Zanchettin, C. and Ludermir, T.B.},
 doi = {10.1142/S0129065705000141},
 journal = {International Journal of Neural Systems},
 number = {1-2}
}

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