Results 61 to 70 of about 1,727,048 (195)
Parallel Nonnegative Matrix Factorization with Manifold Regularization
Journal of Electrical and Computer Engineering, 2018 Nonnegative matrix factorization (NMF) decomposes a high-dimensional nonnegative matrix into the product of two reduced dimensional nonnegative matrices.
Fudong Liu, Zheng Shan, Yihang Chen
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SAR Target Recognition via Incremental Nonnegative Matrix Factorization
Remote Sensing, 2018 In synthetic aperture radar (SAR) target recognition, the amount of target data increases continuously, and thus SAR automatic target recognition (ATR) systems are required to provide updated feature models in real time.
Sihang Dang +3 more
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IEEE Access, 2020 This paper proposes a brand-new method to perform safety monitoring using images for steel coil marking industrial processes. The new safety monitoring method is developed with the aid of a new graph-regularized semi-supervised nonnegative matrix ...
Song Fan, Qilong Jia, Wan Sheng Cheng
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Journal of Chemometrics, Volume 40, Issue 10, October 2026.ABSTRACT The area of feasible solutions (AFS) quantifies factor ambiguity in multivariate curve resolution (MCR). Although AFS computation is well‐defined for noise‐free data, experimental datasets require constraint relaxation and parameter tuning, which influence the resulting feasible bands.
Mathias Sawall +4 more
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Nonparametric Bayesian Nonnegative Matrix Factorization
, 2020 © Springer Nature Switzerland AG 2020. Nonnegative Matrix Factorization (NMF) is an important tool in machine learning for blind source separation and latent factor extraction.
Mengersen, K +9 more
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Nonnegative Reduced Biquaternion Matrix Factorization With Applications in Color Face Recognition
Numerical Linear Algebra with Applications, Volume 33, Issue 5, October 2026.ABSTRACT Quaternion numbers are commonly used to represent color image pixels. Since color image pixels are nonnegative, nonnegativity constraint should be incorporated into the components of quaternion numbers. However, existing quaternion‐based matrix factorization models do not fully satisfy nonnegativity constraints.
Jifei Miao, Junjun Pan, Michael K. Ng
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IEEE Access, 2020 Nonnegative matrix factorization-based image representation algorithms have been widely applied to deal with high-dimensional data in the past few years.
Zhenqiu Shu +4 more
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Impact of the Choice of Normalization Method on Molecular Cancer Class Discovery Using Nonnegative Matrix Factorization. [PDF]
PLoS ONE, 2016 Nonnegative Matrix Factorization (NMF) has proved to be an effective method for unsupervised clustering analysis of gene expression data. By the nonnegativity constraint, NMF provides a decomposition of the data matrix into two matrices that have been ...
Haixuan Yang, Cathal Seoighe
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Latent Multi-View Semi-Nonnegative Matrix Factorization with Block Diagonal Constraint
Axioms, 2022 Multi-view clustering algorithms based on matrix factorization have gained enormous development in recent years. Although these algorithms have gained impressive results, they typically neglect the spatial structures that the latent data representation ...
Lin Yuan +3 more
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Journal of Telecommunications and Information Technology, 2018 Rapid escalation of wireless communication and hands-free telephony creates a problem with acoustic echo in full-duplex communication applications. In this paper a simulation of model-based acoustic echo cancelation and near-end speaker extraction using
Pallavi Agrawal, Madhu Shandilya
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