Results 51 to 60 of about 55,457 (295)
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
doaj +1 more source
Musical instrument classification using non-negative matrix factorization algorithms
, 2006 In this paper, a class of algorithms for automatic classification of individual musical instrument sounds is presented. Several perceptual features used in general sound classification applications were measured for 300 sound recordings consisting of 6 ...
Benetos, E, Kotropoulos, C, Kotti, M
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Algorithms for nonnegative matrix factorization with the beta-divergence [PDF]
, 2011 This paper describes algorithms for nonnegative matrix factorization (NMF) with the beta-divergence (beta-NMF). The beta-divergence is a family of cost functions parametrized by a single shape parameter beta that takes the Euclidean distance, the ...
Févotte, Cédric, Idier, Jérôme
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IEEE Access, 2018 Nonnegative matrix factorization (NMF) technique has been developed successfully to represent the intuitively meaningful feature of data. A suitable representation can faithfully preserve the intrinsic structure of data.
Wenjie Zhu, Yunhui Yan
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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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Bi-Objective Nonnegative Matrix Factorization: Linear Versus Kernel-Based Models
, 2015 Nonnegative matrix factorization (NMF) is a powerful class of feature extraction techniques that has been successfully applied in many fields, namely in signal and image processing.
Honeine, Paul, Zhu, Fei
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An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
Advanced Engineering Materials, EarlyView.An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
wiley +1 more source
Entropy, 2017 Semi-Nonnegative Matrix Factorization (Semi-NMF), as a variant of NMF, inherits the merit of parts-based representation of NMF and possesses the ability to process mixed sign data, which has attracted extensive attention. However, standard Semi-NMF still
Peng Luo, Jinye Peng
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Hidden Markov models as priors for regularized nonnegative matrix factorization in single-channel source separation [PDF]
, 2012 We propose a new method to incorporate rich statistical priors, modeling temporal gain sequences in the solutions of nonnegative matrix factorization (NMF). The proposed method can be used for single-channel source separation (SCSS) applications.
Erdogan, Hakan +2 more
core
Integrating Vibrio natriegens for Photon Manipulation in Living Lighting Devices
Advanced Materials, EarlyView.Rationalization of genetic and material engineering tools has enabled the engineering of fluorescent Vibrio natriegens (V. natriegens) to fabricate straightforward, highly emissive and stable V. natriegens‐silicones color filters for the first red‐emitting bacteria‐hybrid light‐emitting diodes. This pinpoints V. natriegens as a high‐performance protein
Stephanie Willeit +6 more
wiley +1 more source