A Novel Multi-Dimensional Feature Extraction Framework of Data Sampled by Electronic Nose

Mingqi Jin, Wentao Shi, Haoyue Fu, Zewen Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

A feature extraction framework of electronic nose is proposed in this paper. Proposed framework is mainly composed of two parts; the one is the noise reduction subsystem which is described as the cascade connection between wavelet filter and moving average filter, the other is the feature extraction system which can be used to extract the integral feature and difference feature related to output of the noise reduction subsystem. In addition, details related to proposed framework including wavelet basis and its order and slide windows of moving average filter are deeply discussed too. Comparative experiment on real dataset is employed to demonstrate the effectiveness of proposed framework.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665469722
DOIs
StatePublished - 2022
Event2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022 - Xi'an, China
Duration: 25 Oct 202227 Oct 2022

Publication series

Name2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022

Conference

Conference2022 IEEE International Conference on Signal Processing, Communications and Computing, ICSPCC 2022
Country/TerritoryChina
CityXi'an
Period25/10/2227/10/22

Keywords

  • feature extraction
  • moving average filter
  • multi-dimensional feature
  • noise reduction
  • wavelet filter

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