Nonconvex Nonseparable Sparse Nonnegative Matrix Factorization for Hyperspectral Unmixing
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Hyperspectral unmixing is an important step to learn the material categories and corresponding distributions in a scene. Over the past decade, nonnegative matrix factorization (NMF) has been utilized for this task, thanks to its good physical ...
Fengchao Xiong +3 more
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NMF-based stimulus decoding of simulated data.
, 2016 (A) Patterns for spike train generation are plotted with the same conventions as in Fig 2A. Overlap of the patterns is increasing from left to right (overlap 0 to 3).
Jian K. Liu (371544) +5 more
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Underwater acoustic target signal enhancement algorithm optimized by feature preservation and noise update [PDF]
Zhihui kongzhi yu fangzhenThe enhancement effect of the classic Nonnegative Matrix Factorization (NMF) applied to underwater acoustic target signal is unsatisfactory for the feature overlap of underwater acoustic target signal and the variability of ocean underwater acoustic ...
XIAO Haixia, CUI Shuangyue, LI Dawei, SUN Mingming, LIU Xianzhong, YANG Zhenxin
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Robust Semi-Supervised Non-Negative Matrix Factorization With Structured Normalization
IEEE Access, 2019 Non-negative matrix factorization (NMF) approximates a non-negative data matrix with the product of two low-rank non-negative matrices by minimizing the cost of such approximation.
Liujing Wang +4 more
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Hessian Regularization Based Factorization Algorithm Combining Multi-view and Non-negative Matrix [PDF]
Jisuanji gongcheng, 2017 Non-negative matrix does not consider the manifold of data when represents multi-view data,which results in the ineffective express of the data internal expression.In this paper,Hessian regularized Non-negative Matrix Factorization(NMF) is proposed.By ...
WANG Chaofeng,SHI Jun,WU Jinjie,ZHU Jie
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LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates-2
, 2011 Copyright information:Taken from "LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates"BMC Bioinformatics 2006;7():175-175.Published online 28 Mar 2006PMCID:PMC1450309.Copyright © 2006 Wang et al; licensee BioMed
Andrew V Kossenkov (73124) +2 more
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Knowledge Discovery Through Topic Modeling on GoPartner User Reviews Using BERTopic, LDA, and NMF
Journal of Applied Informatics and ComputingTransportation and food delivery services are one of the driving sectors of the digital economy in Indonesia. The e-Conomy SEA 2023 report shows that the transportation and food delivery services sector experienced a decrease in GMV in 2023 by 8% from ...
Metti Detricia Pratiwi, Ken Ditha Tania
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BioMedical Engineering OnLine, 2020 Background Nonnegative matrix factorization (NMF) has been successfully used for electroencephalography (EEG) spectral analysis. Since NMF was proposed in the 1990s, many adaptive algorithms have been developed.
Guoqiang Hu +6 more
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ENDMEMBER EXTRACTION OF HIGHLY MIXED DATA USING L1 SPARSITY-CONSTRAINED MULTILAYER NONNEGATIVE MATRIX FACTORIZATION [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018 Due to the limited spatial resolution of remote hyperspectral sensors, pixels are usually highly mixed in the hyperspectral images. Endmember extraction refers to the process identifying the pure endmember signatures from the mixture, which is an ...
H. Fang +6 more
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LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates-3
, 2011 Copyright information:Taken from "LS-NMF: A modified non-negative matrix factorization algorithm utilizing uncertainty estimates"BMC Bioinformatics 2006;7():175-175.Published online 28 Mar 2006PMCID:PMC1450309.Copyright © 2006 Wang et al; licensee BioMed
Andrew V Kossenkov (73124) +2 more
core +1 more source