An efficient second‐order neural network model for computing the Moore–Penrose inverse of matrices
Abstract The computation of the Moore–Penrose inverse is widely encountered in science and engineering. Due to the parallel‐processing nature and strong‐learning ability, the neural network has become a promising approach to solving the Moore–Penrose inverse recently. However, almost all the existin...
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| Главные авторы: | , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Wiley
2022-12-01
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| Серии: | IET Signal Processing |
| Предметы: | |
| Online-ссылка: | https://doi.org/10.1049/sil2.12156 |
| Метки: |
Нет меток, Требуется 1-ая метка записи!
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