A Multiscale Wavelet Kernel Regularization-Based Feature Extraction Method for Electronic Nose

In the electronic nose (e-nose), a stable feature representation of the gas sensor's response is a key step to realize subsequent odor identification algorithms. However, the noises in gas sensors hinder the acquisition of such features. In order to solve this problem, this article proposes a s...

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Veröffentlicht in:	IEEE transactions on systems, man, and cybernetics. Systems man, and cybernetics. Systems, 2022-11, Vol.52 (11), p.7078-7089
Hauptverfasser:	Liu, Taoping, Zhang, Wentian, Li, Jun, Ueland, Maiken, Forbes, Shari L., Zheng, Wei Xing, Su, Steven Weidong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Australia Electronic nose (e-nose) Electronic noses Experiments Feature extraction Frequency-domain analysis Gas detectors Gas sensors Impulse response Kernel Kernels Monitoring Multiresolution analysis multiscale wavelet kernel regularization odor identification Random noise Regularization Representations Sensors transfer learning
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