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Shift Invariance Property of a Non-Negative Matrix Factorization

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Please use this identifier to cite or link to this item:http://hdl.handle.net/2115/76931

Title: Shift Invariance Property of a Non-Negative Matrix Factorization
Authors: Imai, Hideyuki Browse this author →KAKEN DB
Keywords: non-negative matrix factorization
semi non-negative matrix factorization
parallel moving
Issue Date: Feb-2020
Publisher: 電子情報通信学会(The Institute of Electronics, Information and Communication Engineers / IEICE)
Journal Title: IEICE transactions on fundamentals of electronics communications and computer sciences
Volume: E103-A
Issue: 2
Start Page: 580
End Page: 581
Publisher DOI: 10.1587/transfun.2019EAL2121
Abstract: We consider a property about a result of non-negative matrix factorization under a parallel moving of data points. The shape of a cloud of original data points and that of data points moving parallel to a vector are identical. Thus it is sometimes required that the coefficients to basis vectors of both data points are also identical from the viewpoint of classification. We show a necessary and sufficient condition for such an invariance property under a translation of the data points.
Rights: copyright©2020 IEICE
Relation: http://search.ieice.org/
Type: article
URI: http://hdl.handle.net/2115/76931
Appears in Collections:情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)

Submitter: 今井 英幸

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