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非负矩阵分解算法综述 被引量：105

A Survey on Algorithms of Non-Negative Matrix Factorization
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摘要 本文介绍了非负矩阵分解(Non-negative Matrix Factorization,NMF)的基本原理和性质,将现有NMF算法分为了基于基本NMF模型的算法和基于改进NMF模型的算法两大类,在此基础上较为系统地分析、总结和比较了它们的构造原则、应用特点以及存在的问题,最后预测和分析了未来NMF算法研究的可能方向. The fundamentals and properties of non-negative matrix factorization （NMF） are introduced, and available NMF algorithms are classified into two categories： basic NMF model-based algorithms and improved NMF model-based algorithms, Based on these, the design principles, application characteristics, and existing problems of the algorithms are systematically discussed. Be- sides, some open problems in the development of NMF algorithms are presented and analyzed.
作者 李乐 章毓晋
机构地区 清华信息科学与技术国家实验室
出处 《电子学报》 EI CAS CSCD 北大核心 2008年第4期737-743,共7页 Acta Electronica Sinica
基金 国家自然科学基金(No.60573148)
关键词 非负矩阵分解 多元数据描述 特征提取 non-negative matrix factorization multivariate data representation feature extraction
分类号 TP391 [自动化与计算机技术—计算机应用技术]
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参考文献37

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二级参考文献19

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共引文献33

同被引文献933

引证文献105

二级引证文献451

电子学报
2008年 第4期

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