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3차 텐서기반 MPCA 방법을 이용한 심전도신호의 개인식별

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Author(s)
변영현 이재진 정하영 한하영 곽근창
Issued Date
2018
Keyword
Electrocardiogram Multilinear principal component analysis Individual identification Tensor
Abstract
In this paper, performance of individual identification on electrocardiogram using third-order tensor-based MPCA(Multilinear Principal Component Analysis) is performed. This method preserves the data structure by extracting features directly from the tensor representation without structural transformation of the data due to the vectorization process in order to reduce the dimension. It is also less susceptible to small data problems because it can learn more compact and potentially useful representation, and it can efficiently handle large tensors. Here, the third-order tensor is formed by reordering the one-dimensional electrocardiogram signal into a two-dimensional matrix and then taking the time frame into account. Physionet's PTB(Physikalisch-Technische Bundesanstalt) diagnostic database for performance evaluation is used, and MPCA showed 91.85% accuracy.
Alternative Title
Individual Identification on Electrocardiogram using Third-Order Tensor-Based MPCA
Alternative Author(s)
Yeong-Hyeon Byeon Jae-Jin Lee Ha-Young Jeong Ha-Young Han Keun-Chang Kwak
Publisher
조선대학교 공학기술연구원
Citation
변영현. (2018). 3차 텐서기반 MPCA 방법을 이용한 심전도신호의 개인식별, 공학기술논문지 | Vol.11, No.2 p.151 ~ p.157
Type
Laboratory article
ISSN
2005-3142
URI
https://oak.chosun.ac.kr/handle/2020.oak/16711
https://www.chosun.ac.kr/user/indexSub.do?codyMenuSeq=23376167&siteId=riet&dum=dum&boardId=168878&page=7&command=view&boardSeq=294185&chkBoxSeq=&categoryId=&categoryDepth=&search=&column=null&searchDate1=&searchDate2=&selColumn=&myList=
Appears in Collections:
2018 > Vol.11, No.2
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