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oai:riuma.uma.es:10630/343002026-02-03T11:07:03Zcom_10630_2254col_10630_37953

González-Monroy, Javier Palomo-Ferrer, Esteban José López-Rubio, Ezequiel Gonzalez-Jimenez, Antonio Javier 2024-10-03T11:56:51Z 2024-10-03T11:56:51Z 2016-09-03 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. https://hdl.handle.net/10630/34300 10.1016/j.chemolab.2016.08.011 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. eng open access Gases - Análisis Robótica Olfato Continuous Chemical Classification in Uncontrolled Environments with Sliding Windows. journal article