Results 81 to 90 of about 7,782 (177)
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
doaj +1 more source
Gaussian mixture gain priors for regularized nonnegative matrix factorization in single-channel source separation [PDF]
, 2012 We propose a new method to incorporate statistical priors on the solution of the nonnegative matrix factorization (NMF) for single-channel source separation (SCSS) applications.
Erdogan, Hakan +2 more
core
Distributed Unmixing of Hyperspectral Data With Sparsity Constraint
, 2017 Spectral unmixing (SU) is a data processing problem in hyperspectral remote sensing. The significant challenge in the SU problem is how to identify endmembers and their weights, accurately. For estimation of signature and fractional abundance matrices in
Khoshsokhan, Sara +2 more
core +2 more sources
Journal of Geophysical Research: Machine Learning and Computation, Volume 2, Issue 3, September 2025.Abstract Characterization of induced microseismicity at a carbon dioxide (CO2 ${\text{CO}}_{2}$) storage site is critical for preserving reservoir integrity and mitigating seismic hazards. We apply a multilevel machine learning (ML) approach that combines the nonnegative matrix factorization and hidden Markov model to extract spectral representations ...
Rachel M. Willis +5 more
wiley +1 more source
Approximate Nonnegative Matrix Factorization via Alternating Minimization
, 2004 In this paper we consider the Nonnegative Matrix Factorization (NMF) problem: given an (elementwise) nonnegative matrix $V \in \R_+^{m\times n}$ find, for assigned $k$, nonnegative matrices $W\in\R_+^{m\times k}$ and $H\in\R_+^{k\times n}$ such that $V ...
Finesso, Lorenzo, Spreij, Peter
core +1 more source
Similarity Learning-Induced Symmetric Nonnegative Matrix Factorization for Image Clustering
IEEE Access, 2019 As a typical variation of nonnegative matrix factorization (NMF), symmetric NMF (SNMF) is capable of exploiting information of the cluster embedded in the matrix of similarity.
Wei Yan +3 more
doaj +1 more source
E3S Web of Conferences, 2018 Local damage detection in rotating machine elements is very important problem widely researched in the literature. One of the most common approaches is the vibration signal analysis.
Wodecki Jacek
doaj +1 more source
Document Clustering Based On Max-Correntropy Non-Negative Matrix Factorization [PDF]
, 2014 Nonnegative matrix factorization (NMF) has been successfully applied to many areas for classification and clustering. Commonly-used NMF algorithms mainly target on minimizing the $l_2$ distance or Kullback-Leibler (KL) divergence, which may not be ...
Li, Le +4 more
core
Nonnegative factorization and the maximum edge biclique problem [PDF]
Nonnegative matrix factorization (NMF) is a data analysis technique based on the approximation of a nonnegative matrix with a product of two nonnegative factors, which allows compression and interpretation of nonnegative data. In this paper, we study the
GILLIS, Nicolas, GLINEUR, François
core
A Hybrid Algorithm for Estimating Origin-Destination Flows
IEEE Access, 2018 With the development of intelligent transportation systems, the estimation of traffic flow in urban areas has attracted a great attention of researchers.
Xianghua Li +5 more
doaj +1 more source