RT Journal Article
T1 Continuous Chemical Classification in Uncontrolled Environments with Sliding Windows.
A1 González-Monroy, Javier
A1 Palomo-Ferrer, Esteban José
A1 López-Rubio, Ezequiel
A1 Gonzalez-Jimenez, Antonio Javier
K1 Gases - Análisis
K1 Robótica
K1 Olfato
AB Electronic noses are sensing devices able to classify chemical volatiles according to the readings of an array of non-selective gas sensors and some pattern recognition algorithm. Given their high versatility to host multiple sensors while still being compact and lightweight, e-noses have demonstrated to be a promising technology to real-world chemical recognition, which is our main concern in this work. Under these scenarios, classification is usually carried out on sub-sequences of the main e-nose data stream after a segmentation phase which objective is to exploit the temporal correlation of the e-nose’s data. In this work we analyze to which extent considering segments of delayed samples by means of fixed-length sliding windows improves the classification accuracy. Extensive experimentation over a variety of experimental scenarios and gas sensor types, together with the analysis of the classification accuracy of three state-of-the-art classifiers, support our conclusions and findings. In particular, it has been found that fixed-length sliding windows attain better results than instantaneous sensor values for several classifier models, with a high statistical significance.
PB Elsevier
YR 2016
FD 2016-09-03
LK https://hdl.handle.net/10630/34300
UL https://hdl.handle.net/10630/34300
LA eng
NO Monroy, J. G., Palomo, E. J., López-Rubio, E., & Gonzalez-Jimenez, J. (2016). Continuous chemical classification in uncontrolled environments with sliding windows. Chemometrics and Intelligent Laboratory Systems, 158, 117–129.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 22 ene 2026