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一种增量式非负矩阵分解算法 被引量：3

Incremental Non-negative Matrix Factorization Algorithm
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摘要 针对现有的非负矩阵分解算法在应用于问题规模逐渐增大的情形时,运算规模随之增大、空间和时间效率不高的情况,提出一种增量式非负矩阵分解算法,使用分块矩阵的思想降低运算规模,利用上一步的分解结果参与运算从而避免重复运算。实验结果表明,该算法对节约计算资源是有效的。 When existing Non-negative Matrix Factorization（NMF） algorithm is applied to a problem of incremental scale, the consumption of space and time behaves inefficiency. This paper proposes an Incremental Nonnegative Matrix Factorization（INMF） algorithm, which uses partitioned matrix theory to reduce the computing scale, and uses decomposition results already derived to avoid re-calculating every time. Experimental results show that the algorithm performs efficiently for saving computing resources.
作者 郭立 张守志 汪卫 施伯乐
机构地区 复旦大学计算机科学技术学院
出处 《计算机工程》 CAS CSCD 北大核心 2010年第4期66-68,共3页 Computer Engineering
关键词 非负矩阵分解 矩阵分解 增量式算法 Non-negative Matrix Factorization（NMF） matrix factorization incremental algorithm
分类号 TP311.12 [自动化与计算机技术—计算机软件与理论]
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参考文献11

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同被引文献29

  • 1张耀明.中国太阳能光伏发电产业的现状与前景[J].能源研究与利用,2007(1):1-6. 被引量：66
  • 2Lee D D, Seung H S. Algorithms for Nonnegative Matrix Factorization[C] //Proc. of Conference on Neural Information Processing Systems. Cambridge, USA: MIT Press, 2000: 556-562.
  • 3Lin C J. Projected Gradient Methods for Nonnegative Matrix- factorization[D]. Taipei, China: National Taiwan University, 2005.
  • 4Hoyer P O. Nonnegative Matrix Factorization with Sparseness Constraints[J]. Journal Machine Learning Research, 2004, 5(9): 1457-1469.
  • 5Feng Tao, Li S Z, Shum H Y, et al. Local Nonnegative Matrix Factorization as a Visual Representation[C] //Proc. of the 2nd Int’l Conf. on Development and Learning. Washington D. C., USA: IEEE Computer Society, 2002.
  • 6Nicolas G. Using Underapproximations for Sparse Nonnegative Matrix Factorization[J]. Pattern Recognition, 2010, 43(4): 1676- 1687.
  • 7Yin Haiqing, Liu Hongwei. Nonnegative Matrix Factorization with Bounded Total Variational Regularization for Face Recognition[J]. Pattern Recognition Letters, 2010, 31(16): 2468-2473.
  • 8GHODDAMI H, YAZDANI A. A single-stage three-phase photovohaic system with enhanced maximum power point tracking capability and increased power rating [ J ]. IEEE Transactions on Power Delivery,2011,26(2) :1017-1029.
  • 9YONA A,SENJYU T,FUNABASH! T. Application of recur- rent neural network to short-term-ahead generating power fore- casting for photovoltaic system[ C]. IEEE Power Eng/neering Society General Meeting. 2007 : 1-6.
  • 10RAHMAN MD H, YAMASHIRO S. Novel distributed power generating system of PV-ECaSS using solar energy estimation [J]. IEEE Transactions on Energy Conversion, 2007, 22 (2) : 358-367.

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二级引证文献7

计算机工程
2010年 第4期

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