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Sensors 2012, 12(12), 16182-16193; doi:10.3390/s121216182
Article

Classification of Odorants in the Vapor Phase Using Composite Features for a Portable E-Nose System

1
, 2,*  and 3
Received: 30 August 2012; in revised form: 5 November 2012 / Accepted: 13 November 2012 / Published: 22 November 2012
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Abstract: We present an effective portable e-nose system that performs well even in noisy environments. Considering the characteristics of the e-nose data, we use an image covariance matrix-based method for extracting discriminant features for vapor classification. To construct composite vectors, primitive variables of the data measured by a sensor array are rearranged. Then, composite features are extracted by utilizing the information about the statistical dependency among multiple primitive variables, and a classifier for vapor classification is designed with these composite features. Experimental results with different volatile organic compounds data show that the proposed system has better classification performance than other methods in a noisy environment.
Keywords: e-nose system; vapor classification; composite feature; discriminant features e-nose system; vapor classification; composite feature; discriminant features
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Choi, S.-I.; Jeong, G.-M.; Kim, C. Classification of Odorants in the Vapor Phase Using Composite Features for a Portable E-Nose System. Sensors 2012, 12, 16182-16193.

AMA Style

Choi S-I, Jeong G-M, Kim C. Classification of Odorants in the Vapor Phase Using Composite Features for a Portable E-Nose System. Sensors. 2012; 12(12):16182-16193.

Chicago/Turabian Style

Choi, Sang-Il; Jeong, Gu-Min; Kim, Chunghoon. 2012. "Classification of Odorants in the Vapor Phase Using Composite Features for a Portable E-Nose System." Sensors 12, no. 12: 16182-16193.


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