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...

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Detalles Bibliográficos
Autores principales: Ou, Guojian, Zou, Sai, Liu, Song, Tang, Jianguo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
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

Internet

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

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