PRE-PROCESSING AND PATTERN RECOGNITION METHODS FOR ARTIFICIAL OLFACTION SYSTEMS: A REVIEW
Journal Title: Metrology and Measurement Systems - Year 2005, Vol 12, Issue 1
Abstract
Data analysis is a fundamental part of artificial olfaction systems. Nonetheless, while electrical and mechanical components of electronic noses are deeply investigated and optimised for the specific applications, data analysis is sometimes performed without any critical understanding about hypotheses on which it is funded. Several methodologies were imported into this field and utilised to correlate electronic nose data to the information required for classification purposes. Chemometrics and neural networks are the sources of the most popular methods currently in use. In this paper some of the most used methodologies of data analysis are reviewed and their use for electronic nose data is discussed. Although the discussion is given considering chemical sensor arrays, the conclusions are generic and valid for a broader range of sensor systems.
Authors and Affiliations
CORRADO DI NATALE, EUGENIO MARTINELLI, ARNALDO D'AMICO
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