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Proceedings Paper

Metal ion solutions identification using acoustic plate mode sensors and principal component analysis
Author(s): Fabien J. Josse; Reiner Dahint; Sejal Shah; Egide V. Houndegla
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Paper Abstract

The parameters used to rate acoustic wave-based chemical sensors are sensitivity and selectivity. While sensitivity can be improved by selecting the appropriate sensor device, selectivity still remains a major concern. This is primarily because the analytes under consideration often belong to the same group/class of chemicals. In such cases, the sensor output does not provide enough information to reliably identify, estimate and/or classify the analytes being investigated. As a result, data analysis techniques are used to extract selectivity from the sensor. An approach to analyze sensor signal data using statistical pattern recognition techniques such as principal component analysis and nearest neighbor algorithm is presented.

Paper Details

Date Published: 18 November 1999
PDF: 12 pages
Proc. SPIE 3857, Chemical Microsensors and Applications II, (18 November 1999); doi: 10.1117/12.370271
Show Author Affiliations
Fabien J. Josse, Marquette Univ. (United States)
Reiner Dahint, Univ. Heidelberg (Germany)
Sejal Shah, Marquette Univ. (United States)
Egide V. Houndegla, Marquette Univ. (United States)


Published in SPIE Proceedings Vol. 3857:
Chemical Microsensors and Applications II
Stephanus Buettgenbach, Editor(s)

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