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Odor Discrimination by Similarity Measures of Abstract Odor Factor Maps from Electronic Noses

机译:通过电子鼻抽象气味因子图的相似性度量区分气味

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摘要

The aim of this study is to improve the discrimination performance of electronic noses by introducing a new method for measuring the similarity of the signals obtained from the electronic nose. We constructed abstract odor factor maps (AOFMs) as the characteristic maps of odor samples by decomposition of three-way signal data array of an electronic nose. A similarity measure for two-way data was introduced to evaluate the similarities and differences of AOFMs from different samples. The method was assessed by three types of pipe and powder tobacco samples. Comparisons were made with other techniques based on PCA, SIMCA, PARAFAC and PARAFAC2. The results showed that our method had significant advantages in discriminating odor samples with similar flavors or with high VOCs release.
机译:这项研究的目的是通过引入一种新的方法来测量从电子鼻获得的信号的相似性,从而提高电子鼻的识别性能。我们通过分解电子鼻的三向信号数据阵列,构建了抽象的气味因子图(AOFM)作为气味样本的特征图。引入了双向数据相似性度量,以评估不同样品中AOFM的相似性和差异。该方法通过三种类型的烟斗和粉末烟草样品进行评估。与其他基于PCA,SIMCA,PARAFAC和PARAFAC2的技术进行了比较。结果表明,我们的方法在区分具有相似风味或高挥发性有机化合物的气味样品方面具有显着优势。

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