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 investigat...

Full description

Saved in:
Bibliographic Details
Published in:International journal of neural systems 2005-02, Vol.15 (1n02), p.137-149
Main Authors: ZANCHETTIN, CLEBER, LUDERMIR, TERESA B.
Format: Article
Language:English
Subjects:
Animals
Artificial Organs
Fuzzy Logic
Humans
Neural Networks (Computer)
Nose
Pattern Recognition, Automated - methods
Principal Component Analysis
Smell - physiology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0129-0657
1793-6462
DOI:10.1142/S0129065705000141