Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1166910 | Analytica Chimica Acta | 2010 | 8 Pages |
Abstract
In an electronic tongue, preprocessing on raw data precedes pattern analysis and choice of the appropriate preprocessing technique is crucial for the performance of the pattern classifier. While attempting to classify different grades of black tea using a voltammetric electronic tongue, different preprocessing techniques have been explored and a comparison of their performances is presented in this paper. The preprocessing techniques are compared first by a quantitative measurement of separability followed by principle component analysis; and then two different supervised pattern recognition models based on neural networks are used to evaluate the performance of the preprocessing techniques.
Related Topics
Physical Sciences and Engineering
Chemistry
Analytical Chemistry
Authors
Mousumi Palit, Bipan Tudu, Nabarun Bhattacharyya, Ankur Dutta, Pallab Kumar Dutta, Arun Jana, Rajib Bandyopadhyay, Anutosh Chatterjee,