Drift Compensation on Massive Online Electronic-Nose Responses

Drift Compensation on Massive Online Electronic-Nose Responses

Gas sensor drift is an important issue of electronic nose (E-nose) systems. This study follows this concern under the condition that requires an instant drift compensation with massive online E-nose responses. Recently, an active learning paradigm has been introduced to such condition. However, it d...

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Bibliographic Details
Main Authors: Jianhua Cao, Tao Liu, Jianjun Chen, Tao Yang, Xiuxiu Zhu, Hongjin Wang
Format: Article
Language:English
Published: MDPI AG 2021-04-01
Series:Chemosensors
Subjects:
electronic nose
drift compensation
active learning
noisy label problem
mixed Gaussian model
expected entropy
Online Access:https://www.mdpi.com/2227-9040/9/4/78

Internet

https://www.mdpi.com/2227-9040/9/4/78

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