林秋华

个人信息Personal Information

教授

博士生导师

硕士生导师

性别:女

毕业院校:大连理工大学

学位:博士

所在单位:信息与通信工程学院

学科:信号与信息处理

联系方式:84706002-3326; 84706697

电子邮箱:qhlin@dlut.edu.cn

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Double coupled canonical polyadic decomposition of third-order tensors: Algebraic algorithm and relaxed uniqueness conditions

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论文类型:期刊论文

发表时间:2019-04-01

发表刊物:SIGNAL PROCESSING-IMAGE COMMUNICATION

收录刊物:SCIE

卷号:73

期号:,SI

页面范围:22-36

ISSN号:0923-5965

关键字:Tensor; Canonical polyadic decomposition; Double coupled; Algebraic algorithm; Uniqueness

摘要:Double coupled canonical polyadic decomposition (DC-CPD) decomposes multiple tensors with coupling in the first two modes, into minimal number of rank-1 tensors that also admit the double coupling structure. It has a particular interest in joint blind source separation (J-BSS) applications. In a preceding paper, we proposed an algebraic algorithm for underdetermined DC-CPD, of which the factor matrices in the first two modes of each tensor may have more columns than rows. It uses a pairwise coupled rank-1 detection mapping to transform a possibly underdetermined DC-CPD into an overdetermined DC-CPD, which can be solved algebraically via generalized eigenvalue decomposition (GEVD). In this paper, we generalize the pairwise or second-order coupled rank-1 detection mapping to an arbitrary order K >= 2. Based on this generalized coupled rank-1 detection mapping, we propose a broad framework for the algebraic computation of DC-CPD, which consists of a series of algorithms with more relaxed working assumptions, each corresponding to a fixed order K >= 2. Deterministic and generic uniqueness conditions are provided. We will show through analysis and numerical results that our new uniqueness conditions for DC-CPD are more relaxed than the existing results for DC-CPD and CPD. We will further show, through simulation results, the performance of the proposed algebraic DC-CPD framework in approximate DC-CPD and a J-BSS application, in comparison with existing DC-CPD and CPD algorithms.