Dictionary-Based Tensor Canonical Polyadic Decomposition

To ensure interpretability of extracted sources in tensor decomposition, we introduce in this paper a dictionary-based tensor canonical polyadic decomposition, which enforces one factor to belong exactly to a known dictionary. A new formulation of sparse coding is proposed, which enables high-dimens...

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Veröffentlicht in:	IEEE transactions on signal processing 2018-04, Vol.66 (7), p.1876-1889
Hauptverfasser:	Cohen, Jeremy Emile, Gillis, Nicolas
Format:	Artikel
Sprache:	eng
Schlagworte:	constrained optimization Data models Dictionaries Encoding Engineering Sciences Indexes Matrix decomposition multiway analysis Signal and Image processing Source separation sparse coding spectral unmixing Tensile stress Tensor
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