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Sensors 2014, 14(4), 6938-6951; doi:10.3390/s140406938

A Discriminant Distance Based Composite Vector Selection Method for Odor Classification

1
Department of Applied Computer Engineering, Dankook University, 126 Jukjeon-dong, Suji-gu, Yongin-si, Gyeonggi-do 448-701, Korea
2
Electrical Engineering, Kookmin University 2, 861-1, Jeongeung-dong, Songbuk-gu, Seoul 136-702, Korea
*
Author to whom correspondence should be addressed.
Received: 9 January 2014 / Revised: 25 March 2014 / Accepted: 9 April 2014 / Published: 17 April 2014
(This article belongs to the Section Chemical Sensors)
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Abstract

We present a composite vector selection method for an effective electronic nose system that performs well even in noisy environments. Each composite vector generated from a electronic nose data sample is evaluated by computing the discriminant distance. By quantitatively measuring the amount of discriminative information in each composite vector, composite vectors containing informative variables can be distinguished and the final composite features for odor classification are extracted using the selected composite vectors. Using the only informative composite vectors can be also helpful to extract better composite features instead of using all the generated composite vectors. Experimental results with different volatile organic compound data show that the proposed system has good classification performance even in a noisy environment compared to other methods. View Full-Text
Keywords: distance discriminant; composite vector; odor classification; sensor array; electronic nose distance discriminant; composite vector; odor classification; sensor array; electronic nose
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This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Choi, S.-I.; Jeong, G.-M. A Discriminant Distance Based Composite Vector Selection Method for Odor Classification. Sensors 2014, 14, 6938-6951.

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