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Canonical Polyadic Decomposition Based on a Single Mode Blind Source Separation

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2 Author(s)
Guoxu Zhou ; Lab. for Adv. Brain Signal Process., RIKEN BSI, Wako, Japan ; Cichocki, A.

A new canonical polyadic (CP) decomposition method is proposed in this letter, where one factor matrix is extracted first by using any standard blind source separation (BSS) method and the remainder components are computed efficiently via sequential singular value decompositions of rank-1 matrices. The new approach provides more interpretable factors and it is extremely efficient for ill-conditioned problems. Especially, it overcomes the bottleneck problems, which often cause very slow convergence speed in CP decompositions. Simulations confirmed the validity and efficiency of the proposed method.

Published in:

Signal Processing Letters, IEEE  (Volume:19 ,  Issue: 8 )