Cancellation of chemical backgrounds with generalized Fisher's linear discriminants

R. Gutierrez-Osuna, B. Raman

Research output: Contribution to conferencePaperpeer-review

5 Scopus citations


This article presents a signal-processing technique capable of canceling the effect of background chemicals from the multivariate response of a sensor array. We propose a generalization of the Fisher's eigenvalue solution that minimizes the discrimination between undesirable chemicals and a neutral reference. The proposed technique is a generalization of an earlier model that was limited to the removal of single volatiles. A reformulation of class memberships allows the new model to cancel the effect of both single and mixture backgrounds. The model is validated on experimental data from an array of temperature-modulated metal-oxide sensors exposed to binary and ternary mixtures.

Original languageEnglish
Number of pages4
StatePublished - 2004
EventIEEE Sensors 2004 - Vienna, Austria
Duration: Oct 24 2004Oct 27 2004


ConferenceIEEE Sensors 2004


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