Cargando…
Speech Compressive Sampling Using Approximate Message Passing and a Markov Chain Prior
By means of compressive sampling (CS), a sparse signal can be efficiently recovered from its far fewer samples than that required by the Nyquist–Shannon sampling theorem. However, recovering a speech signal from its CS samples is a challenging problem, as it is not sparse enough on any existing cano...
Autores principales: | Jia, Xiaoli, Liu, Peilin, Jiang, Sumxin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7472005/ https://www.ncbi.nlm.nih.gov/pubmed/32824410 http://dx.doi.org/10.3390/s20164609 |
Ejemplares similares
-
Approximating countable Markov chains
por: Freedman, David
Publicado: (1983) -
Approximate quantum Markov chains
por: Sutter, David
Publicado: (2018) -
Neuronal message passing using Mean-field, Bethe, and Marginal approximations
por: Parr, Thomas, et al.
Publicado: (2019) -
Extended Variational Message Passing for Automated Approximate Bayesian Inference
por: Akbayrak, Semih, et al.
Publicado: (2021) -
Universal recovery map for approximate Markov chains
por: Sutter, David, et al.
Publicado: (2016)