On the study of feature extraction methods for an electronic nose

Year: 2002

Authors: Distante C., Leo M., Siciliano M., Persaud K.C.

Autors Affiliation: CNR, Ist Microelettr & Microsistemi IMM, Via Arnesano, I-73100 Lecce, Italy;
CNR, Inst Studi Sistemi Intelligenti Automaz ISSIA, I-70126 Bari, Italy;
Instrumentation and Analytical Science DIAS-UMIST, Manchester M60 1QD, Lancs, England

Abstract: In this study, we analyzed the transient of microsensors based on tin oxide sol-gel thin film. A novel method to this research field for data analysis and discrimination among different volatile organic compounds is presented. Moreover; several feature extraction methods have been considered, both steady-state (fractional change, relative, difference and log) and transient (Fourier and wavelet descriptors, integral and derivatives) information. Feature extraction methods have been validated qualitatively (by using principal component analysis) and quantitatively on the classification rate (by using a radial basis function neural network). (C) 2002 Elsevier Science B.V. All rights reserved.

Journal/Review: SENSORS AND ACTUATORS B-CHEMICAL

Volume: 87 (2)      Pages from: 278  to: 288

More Information: DOI: 10.1016/S0925-4005(02)00247-2
KeyWords: electronic nose; radial basis function; wavelet analysis; feature extraction;
DOI: 10.1016/S0925-4005(02)00247-2

ImpactFactor: 1.893
Citations: 140
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