Results 31 to 40 of about 1,628,183 (185)
Spectro-temporal post-enhancement using MMSE estimation in NMF based single-channel source separation [PDF]
, 2013 We propose to use minimum mean squared error (MMSE) estimates to enhance the signals that are separated by nonnegative matrix factorization (NMF). In single channel source separation (SCSS), NMF is used to train a set of basis vectors for each source ...
Erdoğan, Hakan, Grais, Emad Mounir
core +1 more source
IEEE Access, 2020 Community detection is a critical issue in the field of complex networks. Recently, the nonnegative matrix factorization (NMF) method has successfully uncovered the community structure in the complex networks.
Hong Lu +3 more
doaj +1 more source
Hyperspectral Unmixing Based on Nonnegative Matrix Factorization: A Comprehensive Review
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022 Hyperspectral unmixing has been an important technique that estimates a set of endmembers and their corresponding abundances from a hyperspectral image (HSI).
Xin-Ru Feng +5 more
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Big Data Mining and AnalyticsNonnegative Matrix Factorization (NMF) is one of the most popular feature learning technologies in the field of machine learning and pattern recognition. It has been widely used and studied in the multi-view clustering tasks because of its effectiveness.
Guosheng Cui +3 more
doaj +1 more source
Complexity, 2019 Nonnegative Matrix Factorization (NMF) is a significant big data analysis technique. However, standard NMF regularized by simple graph does not have discriminative function, and traditional graph models cannot accurately reflect the problem of ...
Yong-Jing Hao +4 more
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Business Strategy and the Environment, EarlyView.ABSTRACT Widespread digital adoption has challenged our understanding of how these tools reshape collaboration, trust and sustainability outcomes across different institutional and network contexts. As networks now pursue resilience and sustainable development in parallel, we map emerging research directions and identify how collaboration and ...
Ari Carisza Graha Prasetia +1 more
wiley +1 more source
, 2013 Cochlear implants (CIs) require efficient speech processing to maximize information transmission to the brain, especially in noise. A novel CI processing strategy was proposed in our previous studies, in which sparsity-constrained non-negative matrix ...
Mark Lutman +7 more
core +1 more source
NIMFA: A Python Library for Nonnegative Matrix Factorization [PDF]
, 2012 NIMFA is an open-source Python library that provides a unified interface to nonnegative matrix factorization algorithms. It includes implementations of state-of-the-art factorization methods, initialization approaches, and quality scoring.
Zupan, Blaz, Zitnik, Marinka
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Nanoscale Mapping of Transition Metal Ordering in Individual LiNi0.5Mn1.5O4 Particles Using 4D‐STEM
Small Methods, EarlyView.ABSTRACT The electrochemical performance of the spinel LiNi0.5Mn1.5O4, a high‐voltage positive electrode material for Li‐ion batteries (LIBs), is influenced by the transition metal arrangement in the octahedral network, leading to disordered (Fd3̲m$Fd\underline 3 m$ S.G.) and ordered (P4332 S.G.) structures.
Gozde Oney +10 more
wiley +1 more source
IEEE AccessNonnegative matrix factorization (NMF) is an effective dimensionality reduction and representation learning technique that captures the intrinsic structure of nonnegative data by learning low-dimensional, parts-based representations.
Xuzhu Shen, Jie Li
doaj +1 more source