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...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1979. - 42(2020), 4 vom: 10. Apr., Seite 925-938
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| Auteur principal: |
Lu, Canyi
(Auteur) |
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| Autres auteurs: |
Feng, Jiashi,
Chen, Yudong,
Liu, Wei,
Lin, Zhouchen,
Yan, Shuicheng |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2020
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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