北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2014, Vol. 37 ›› Issue (4): 29-33.doi: 10.13190/j.jbupt.2014.04.000

• 论文 • 上一篇    下一篇

一种新的PARAFAC模型拟合算法

杜建和, 袁超伟, 韩曦   

  1. 北京邮电大学 信息与通信工程学院, 北京 100876
  • 收稿日期:2013-07-31 出版日期:2014-08-28 发布日期:2014-08-09
  • 作者简介:杜建和(1984-),男,博士生,E-mail:dujianhe1@163.com;袁超伟(1960-),男,教授,博士生导师,E-mail:yuancw2000@bupt.edu.cn.
  • 基金资助:

    国家高技术研究发展计划项目(2014AA01A701);国家自然科学基金项目(60872149)

An Improved Algorithm for PARAFAC Model Fittings

DU Jian-he, YUAN Chao-wei, HAN Xi   

  1. School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2013-07-31 Online:2014-08-28 Published:2014-08-09

摘要:

为了提高二线性迭代最小二乘(BALS)算法拟合平行因子(PARAFAC)模型的速度,提出了一种新的PARAFAC模型拟合算法. 该算法利用新迭代与旧迭代之间的增量值,来预测下一次迭代的初始值,对BALS中的每次迭代,为2个加载矩阵设置相应的松弛因子,并通过联合优化的方法求得最优松弛因子对,从而加速BALS的收敛速度. 理论分析与仿真结果表明,与已有的BALS算法相比,所提算法在不牺牲性能的条件下,有效地提高了PARAFAC模型的拟合速度.

关键词: 二线性迭代最小二乘, 平行因子, 迭代, 松弛因子, 收敛

Abstract:

To speed up the convergence of the bilinear alternating least squares (BALS) algorithm of fitting the parallel factor (PARAFAC) model, an improved algorithm of fitting the PARAFAC model was proposed. In each iteration, the proposed algorithm sets up their own relaxation factors for two loading matrices which are required to be estimated, and gets the optimal couple of two relaxation factors by the joint optimization. Analysis and simulation show that the proposed algorithm improves the speed of fitting the PARAFAC model without performance deterioration compared with the existing BALS algorithm.

Key words: bilinear alternating least squares, parallel factor, iteration, relaxation factor, convergence

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