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首页> 外文期刊>SIAM Journal on Matrix Analysis and Applications >NEW UNIQUENESS CONDITIONS FOR THE CANONICAL POLYADIC DECOMPOSITION OF THIRD-ORDER TENSORS
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NEW UNIQUENESS CONDITIONS FOR THE CANONICAL POLYADIC DECOMPOSITION OF THIRD-ORDER TENSORS

机译:三阶张量的规范多角度分解的新唯一性条件

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摘要

The uniqueness properties of the canonical polyadic decomposition (CPD) of higher-order tensors make it an attractive tool for signal separation. However, CPD uniqueness is not yet fully understood. In this paper, we first present a new uniqueness condition for a polyadic decomposition (PD) where one of the factor matrices is assumed to be known. We also show that this result can be used to obtain a new overall uniqueness condition for the CPD. In signal processing the CPD factor matrices are often constrained. Building on the preceding results, we provide a new uniqueness condition for a CPD with a columnwise orthonormal factor matrix, representing uncorrelated signals. We also obtain a new uniqueness condition for a CPD with a partial Hermitian symmetry, useful for tensors in which covariance matrices are stacked, which are common in statistical signal processing. We explain that such constraints can lead to more relaxed uniqueness conditions. Finally, we provide an inexpensive algorithm for computing a PD with a known factor matrix that is also useful for the computation of the full CPD.
机译:高阶张量的规范多态分解(CPD)的独特性使其成为用于信号分离的有吸引力的工具。但是,CPD的唯一性尚未完全了解。在本文中,我们首先提出了假设条件因子矩阵之一已知的多元分解(PD)的新唯一性条件。我们还表明,该结果可用于获得CPD的新的整体唯一性条件。在信号处理中,经常会限制CPD因子矩阵。在前面的结果的基础上,我们为CPD提供了一个新的唯一性条件,该CPD具有按列正交因子矩阵表示的不相关信号。我们还获得了具有部分Hermitian对称性的CPD的新的唯一性条件,该条件对于在统计信号处理中很常见的堆叠有协方差矩阵的张量很有用。我们解释说,这样的约束可以导致更宽松的唯一性条件。最后,我们提供了一种便宜的算法来计算带有已知因子矩阵的PD,这对于计算完整CPD也很有用。

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