A Sparse Variable Step-Size Least-Mean-Square Algorithm for Impulsive Noise in a Code-Division Multiple Access System
The conventional least-mean-square (LMS) algorithm has a poor performance when the input autocorrelation’s eigenvalue spread is quite large. For instance, the cost function is inadequately described when impulsive noise is present, making it impossible for the LMS approach to correctly identi...
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| Auteurs principaux: | , , , |
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| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
IEEE
2025-01-01
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| Collection: | IEEE Access |
| Sujets: | |
| Accès en ligne: | https://ieeexplore.ieee.org/document/11003947/ |
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