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首页> 外文期刊>IEEE Transactions on Signal Processing: A publication of the IEEE Signal Processing Society >Independent Component Analysis and (Simultaneous) Third-Order Tensor Diagonalization
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Independent Component Analysis and (Simultaneous) Third-Order Tensor Diagonalization

机译:Independent Component Analysis and (Simultaneous) Third-Order Tensor Diagonalization

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摘要

Comon's well-known scheme for independent component analysis (ICA) is based on the maximal diagonalization, in a least-squares sense, of a higher-order cumulant tensor. In a previous papr, we proved that for fourth-order cumulants, the computation of an elementary Jacobi rotation is equivalent to the computation of the best rank-1 approximation of a fourth-order tensor. In this paper, we show that for third-order tensors, the computation of an elementary Jacobi-rotation is again equivalent to a best rank-1 approximation; however, here, it is a matrix that has to be approximated. This favorable computational load makes it attractive to do "something third-order-like" for fourth-order cumulant tensors as well. We show that simultaneous optimal diagonalization of "third-order tensor slices" of the fourth-order cumulant is a suitable strategy. This "simultaneous third-order tensor diago-nalization" approach (STOTD) is similar in spirit to the efficient JADE-algorithm.

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