title: A Novel Feature Extraction Approach Using Window Function Capturing and QPSO-SVM for Enhancing Electronic Nose Performance.
abstract: In this paper, a novel feature extraction approach which can be referred to as moving window function capturing (MWFC) has been proposed to analyze signals of an electronic nose (E-nose) used for detecting types of infectious pathogens in rat wounds. Meanwhile, a quantum-behaved particle swarm optimization (QPSO) algorithm is implemented in conjunction with support vector machine (SVM) for realizing a synchronization optimization of the sensor array and SVM model parameters. The results prove the efficacy of the proposed method for E-nose feature extraction, which can lead to a higher classification accuracy rate compared to other established techniques. Meanwhile it is interesting to note that different classification results can be obtained by changing the types, widths or positions of windows. By selecting the optimum window function for the sensor response, the performance of an E-nose can be enhanced.
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. swugxz@163.com.
authors.forename: Xiuzhen
authors.initials: X
authors.lastname: Guo
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. pengchaocg@163.com.
authors.forename: Chao
authors.initials: C
authors.lastname: Peng
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. z574066616@163.com.
authors.forename: Songlin
authors.initials: S
authors.lastname: Zhang
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. yanjia119@163.com.
authors.forename: Jia
authors.initials: J
authors.lastname: Yan
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. duansk@swu.edu.cn.
authors.forename: Shukai
authors.initials: S
authors.lastname: Duan
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. ldwang@swu.edu.cn.
authors.forename: Lidan
authors.initials: L
authors.lastname: Wang
authors.affiliation: College of Electronics and Information Engineering, Southwest University, Chongqing 400715, China. jiapengfei200609@126.com.
authors.forename: Pengfei
authors.initials: P
authors.lastname: Jia
authors.affiliation: College of Communication Engineering, Chongqing University, Chongqing 400044, China. FengchunTian@cqu.edu.cn.
authors.forename: Fengchun
authors.initials: F
authors.lastname: Tian
mesh_terms: D000818:Animals; D001419:Bacteria / Q000737:chemistry / Q000378:metabolism; D062609:Electronic Nose; D005740:Gases / Q000032:analysis* / Q000378:metabolism; D008297:Male; D051381:Rats; D017207:Rats, Sprague-Dawley; D012815:Signal Processing, Computer-Assisted; D060388:Support Vector Machine; D014946:Wound Infection / Q000382:microbiology
chemical_list: D005740:Gases
keywords: MWFC; QPSO; SVM; electronic nose; feature extraction