title: Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea.
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.
authors: Department of Electronics and Telecommunication Engineering, Central Calcutta Polytechnic, Kolkata 700014, India.
authors: Mousumi
authors: M
authors: Palit
authors: Bipan
authors: B
authors: Tudu
authors: Nabarun
authors: N
authors: Bhattacharyya
authors: Ankur
authors: A
authors: Dutta
authors: Pallab Kumar
authors: PK
authors: Dutta
authors: Arun
authors: A
authors: Jana
authors: Rajib
authors: R
authors: Bandyopadhyay
authors: Anutosh
authors: A
authors: Chatterjee