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| Auteurs principaux: | , , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2407.16925 |
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| _version_ | 1866909266780094464 |
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| author | Wang, Mengyu Zhou, Jingchun Li, Hanyu |
| author_facet | Wang, Mengyu Zhou, Jingchun Li, Hanyu |
| contents | We first propose a concise singular value decomposition of dual matrices. Then, the randomized version of the decomposition is presented. It can significantly reduce the computational cost while maintaining the similar accuracy. We analyze the theoretical properties and illuminate the numerical performance of the randomized algorithm. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_16925 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Randomized dual singular value decomposition Wang, Mengyu Zhou, Jingchun Li, Hanyu Numerical Analysis We first propose a concise singular value decomposition of dual matrices. Then, the randomized version of the decomposition is presented. It can significantly reduce the computational cost while maintaining the similar accuracy. We analyze the theoretical properties and illuminate the numerical performance of the randomized algorithm. |
| title | Randomized dual singular value decomposition |
| topic | Numerical Analysis |
| url | https://arxiv.org/abs/2407.16925 |