Graphical interpretation of non-negative factorization expecting bio-Raman research

被引:1
|
作者
Yu, Hua [1 ]
Wang, Ziteng [1 ]
Nemoto, Mana [2 ]
Suzuta, Kazuyuki [3 ]
Ito, Len [3 ]
Morita, Shin-ichi [1 ]
机构
[1] Tohoku Univ, Grad Sch Sci, Aoba Ku, 6-3 Aramaki Aza Aoba, Sendai, Miyagi 9808578, Japan
[2] Tohoku Univ, Grad Sch Engn, Aoba Ku, 6-6 Aramaki Aza Aoba, Sendai, Miyagi 9808579, Japan
[3] Milbon, Res & Dev Dept, Miyakojima Ku, 2-3-35 Zengenji Cho, Osaka, Osaka 5340015, Japan
关键词
non-negative matrix factorization; NMF; bio; Raman; spectra; BACKGROUND REMOVAL; IN-VIVO; CELLS; SENSITIVITY; DYNAMICS;
D O I
10.35848/1882-0786/ac0fb7
中图分类号
O59 [应用物理学];
学科分类号
摘要
Non-negative matrix factorization (NMF) has been frequently used in research on live cells, biomolecules, and tissues (bio-Raman research) to disentangle the complicated and large sized data. A stagnation is that NMF does not provide unique decomposition, depending on initial settings; that is, NMF returns non-negative spectral components close to the truths, but solely giving several possibilities. In this research, we visualized possible ranges of NMF in binary component system. The mechanism of NMF became more clarified and opened new viewpoints.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] Bio-Raman non-negative matrix factorization: its practical methodology
    He, Jianhai
    Abdel-Galeil, Mohamed M.
    Nemoto, Mana
    Kishimoto, Naoki
    Morita, Shin-ichi
    APPLIED PHYSICS EXPRESS, 2023, 16 (02)
  • [2] Bio-Raman research using principal component analysis and non-negative matrix factorization on rice grains: detections of ordered and disordered states of starch in the cooking process
    Wang, Ziteng
    He, Mengmeng
    Sari, Wulan Intan
    Kishimoto, Naoki
    Morita, Shin-ichi
    JAPANESE JOURNAL OF APPLIED PHYSICS, 2021, 60 (06)
  • [3] Dropout non-negative matrix factorization
    Zhicheng He
    Jie Liu
    Caihua Liu
    Yuan Wang
    Airu Yin
    Yalou Huang
    Knowledge and Information Systems, 2019, 60 : 781 - 806
  • [4] ON FACTORIZATION OF NON-NEGATIVE DEFINITE MATRICRS
    FREIDLIN, MI
    THEORY OF PROBILITY AND ITS APPLICATIONS,USSR, 1968, 13 (02): : 354 - &
  • [5] Non-negative Multiple Tensor Factorization
    Takeuchi, Koh
    Tomioka, Ryota
    Ishiguro, Katsuhiko
    Kimura, Akisato
    Sawada, Hiroshi
    2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), 2013, : 1199 - 1204
  • [6] Non-negative matrix factorization on kernels
    Zhang, Daoqiang
    Zhou, Zhi-Hua
    Chen, Songcan
    PRICAI 2006: TRENDS IN ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2006, 4099 : 404 - 412
  • [7] Non-negative matrix factorization with orthogonality constraints and its application to raman spectroscopy
    Li, Hua Liang
    Adali, Tu Lay
    Wang, Wei
    JOURNAL OF VLSI SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY, 2007, 48 (1-2): : 83 - 97
  • [8] Non-negative Matrix Factorization with Orthogonality Constraints and its Application to Raman Spectroscopy
    Hualiang Li
    Tülay Adal
    Wei Wang
    Darren Emge
    Andrzej Cichocki
    Andrzej Cichocki
    The Journal of VLSI Signal Processing Systems for Signal, Image, and Video Technology, 2007, 48 : 83 - 97
  • [9] INFINITE NON-NEGATIVE MATRIX FACTORIZATION
    Schmidt, Mikkel N.
    Morup, Morten
    18TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO-2010), 2010, : 905 - 909
  • [10] Collaborative Non-negative Matrix Factorization
    Benlamine, Kaoutar
    Grozavu, Nistor
    Bennani, Younes
    Matei, Basarab
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2019: TEXT AND TIME SERIES, PT IV, 2019, 11730 : 655 - 666