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A secondary EWMA-based dictionary learning algorithm for polynomial phase signal denoising
Under the influence of additive white Gaussian noise, sparse representation cannot effectively remove noise associated with the polynomial phase signal (PPS) via most dictionary learning algorithms whose training data come from the noisy signal, such as K-SVD and RLS-DLA. In this paper, we present a...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392793/ https://www.ncbi.nlm.nih.gov/pubmed/35987758 http://dx.doi.org/10.1038/s41598-022-16644-y |