...
首页> 外文期刊>Signal Processing. Image Communication: A Publication of the the European Association for Signal Processing >Double coupled canonical polyadic decomposition of third-order tensors: Algebraic algorithm and relaxed uniqueness conditions
【24h】

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

机译:三阶张量的双耦合规范多adic分解:代数算法和休闲唯一性条件

获取原文
获取原文并翻译 | 示例
           

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.
机译:双耦合规范多adic分解(DC-CPD)将多个张量分解在前两种模式中的耦合,进入最小数量的秩-1张量,这也承认了双耦合结构。它对联合盲源分离(J-BSS)应用具有特别兴趣。在前面的纸张中,我们提出了一种用于未确定的DC-CPD的代数算法,其中每个张量的前两种模式中的因子矩阵可以具有比行更多的列。它使用成对耦合的秩1检测映射以将可能未定的DC-CPD转换为过度定义的DC-CPD,其可以通过广义特征值分解(GEVD)来解决代数求解。在本文中,我们将成对或二阶耦合等级-1检测映射概括为任意顺序k> = 2.基于该广义耦合秩-1检测映射,我们提出了一种广泛的DC - 代数计算框架CPD,由一系列具有更轻松的工作假设的一系列算法,每个算法对应于固定阶K> = 2.提供确定性和通用唯一性条件。我们将通过分析和数值结果来展示我们的DC-CPD的新唯一性条件比DC-CPD和CPD的现有结果更加轻松。我们将通过仿真结果进一步显示,与现有的DC-CPD和CPD算法相比,我们将通过仿真结果,在近似的DC-CPD和J-BSS应用中进行拟议的代数DC-CPD框架。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号