NDLI: An improved EEMD model for feature extraction and classification of gunshot in public places

Content Provider	IEEE Xplore Digital Library
Author	Zhilong Zhang Weihong Li Weiguo Gong Jianhua Zhong
Copyright Year	2012
Description	Author affiliation: Key lab of Optoelectronic Technology and Systems of Education Ministry, Chongqing University, Chongqing, China (Zhilong Zhang; Weihong Li; Weiguo Gong) \|\| Chongqing Metro Corporation, Chongqing, China (Jianhua Zhong)
Abstract	Ensemble empirical mode decomposition (EEMD) is a noise-assisted adaptive data analysis method. The key of EEMD is to add Gauss white noise into the signal to overcome mode-mixing problem caused by original empirical mode decomposition (EMD). Because the noise in public places is natural noise with alpha stable distribution, in this paper we proposes an improved EEMD by using symmetric alpha stable (SaS) distribution instead of the Gauss distribution, and applies the improved EEMD for extracting gunshot feature. Using the improved EEMD, firstly we decompose gunshot signals into a finite number of intrinsic mode functions (IMF). Then, we use the energy ratio of each IMF components to original signal as gunshot feature for classification. The results of simulating experiment show that the improved EEMD method has good generalization abilities for the feature extraction of gunshot in public noise places.
Starting Page	1517
Ending Page	1520
File Size	651159
Page Count	4
File Format	PDF
ISBN	9781467322164
ISSN	10514651
e-ISBN	9784990644109
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-11
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	ICPR Org Committee
Subject Keyword	Feature extraction Mel frequency cepstral coefficient Empirical mode decomposition Training White noise Signal to noise ratio energy ratio Feature extraction of gunshot ensemble empirical mode decomposition (EEMD) symmetric alpha stable distribution IMF components
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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