A data selection method applied to on-line drift compensation for gas sensors
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Abstract:
A new data culling and labeling method is proposed to avoid misleading outcomes caused by multi-state samples during drift compensation process. This method culls data by the curve slops of gas sensor array response and labels data by comparing input samples with the memories of pattern recognition algorithm to avoid occurrence of misleading results. Experiments show the method combined with on-line drift compensation algorithm can estimate sample-states automatically and increase the recognizing accuracy from 37.5% to 100%.
