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Sensors 2010, 10(11), 10387-10400; doi:10.3390/s101110387

Data Refinement and Channel Selection for a Portable E-Nose System by the Use of Feature Feedback

1
School of Electrical Engineering and Computer Science, Seoul National University 1, #047, San 56-1, Sillim-dong, Gwanak-gu, Seoul 151-744, Korea
2
Electrical Engineering, Kookmin University 2, 861-1, Jeongeung-dong, Songbuk-gu, Seoul 136-702, Korea
3
Biomedical Engineering, Chonbuk National University 3, 664-14, Iga Deokjin-dong, Jeonju, Korea
*
Author to whom correspondence should be addressed.
Received: 17 September 2010 / Revised: 25 October 2010 / Accepted: 1 November 2010 / Published: 17 November 2010
(This article belongs to the Section Chemical Sensors)
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Abstract

We propose a data refinement and channel selection method for vapor classification in a portable e-nose system. For the robust e-nose system in a real environment, we propose to reduce the noise in the data measured by sensor arrays and distinguish the important part in the data by the use of feature feedback. Experimental results on different volatile organic compounds data show that the proposed data refinement method gives good clustering for different classes and improves the classification performance. Also, we design a new sensor array that consists only of the useful channels. For this purpose, each channel is evaluated by measuring its discriminative power based on the feature mask used in the data refinement. Through the experimental results, we show that the new sensor array improves both the classification rates and the efficiency in computation and data storage. View Full-Text
Keywords: e-nose system; vapor classification; feature feedback; discriminant feature e-nose system; vapor classification; feature feedback; discriminant feature
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Choi, S.-I.; Kim, S.-H.; Yang, Y.; Jeong, G.-M. Data Refinement and Channel Selection for a Portable E-Nose System by the Use of Feature Feedback. Sensors 2010, 10, 10387-10400.

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