Journal
SENSORS
Volume 10, Issue 11, Pages 10387-10400Publisher
MDPI
DOI: 10.3390/s101110387
Keywords
e-nose system; vapor classification; feature feedback; discriminant feature
Funding
- Kookmin University, Korea
- MKE (The Ministry of Knowledge Economy), Korea, under the ITRC (Information Technology Research Center) [NIPA-2010-C1090-1021-0005]
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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.
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