Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

Pattern Classification Using an Olfactory Model with PCA Feature Selection in Electronic Noses: Study and Application

Biologically-inspired models and algorithms are considered as promising sensor array signal processing methods for electronic noses. Feature selection is one of the most important issues for developing robust pattern recognition models in machine learning. This paper describes an investigation into...

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Bibliographic Details
Main Authors: Junbao Zheng, Jianguo Xing, Canqin Huang, Jun Fu
Format: Article
Language:English
Published: MDPI AG 2012-03-01
Series:Sensors
Subjects:
artificial neural network
olfactory model
feature selection
principal component analysis
pattern classification
electronic nose
Online Access:http://www.mdpi.com/1424-8220/12/3/2818/

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http://www.mdpi.com/1424-8220/12/3/2818/

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