Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm
In this paper, we consider the Tensor Robust Principal Component Analysis (TRPCA) problem, which aims to exactly recover the low-rank and sparse components from their sum. Our model is based on the recently proposed tensor-tensor product (or t-product) [14]. Induced by the t-product, we first rigoro...
Ausführliche Beschreibung
Bibliographische Detailangaben
| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 42(2020), 4 vom: 10. Apr., Seite 925-938
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| 1. Verfasser: |
Lu, Canyi
(VerfasserIn) |
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| Weitere Verfasser: |
Feng, Jiashi,
Chen, Yudong,
Liu, Wei,
Lin, Zhouchen,
Yan, Shuicheng |
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| Format: | Online-Aufsatz
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| Sprache: | English |
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| Veröffentlicht: |
2020
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on pattern analysis and machine intelligence
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| Schlagworte: | Journal Article |
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