Cargando…
Bayesian Compressive Sensing of Sparse Signals with Unknown Clustering Patterns
We consider the sparse recovery problem of signals with an unknown clustering pattern in the context of multiple measurement vectors (MMVs) using the compressive sensing (CS) technique. For many MMVs in practice, the solution matrix exhibits some sort of clustered sparsity pattern, or clumpy behavio...
Autores principales: | Shekaramiz, Mohammad, Moon, Todd K., Gunther, Jacob H. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514728/ https://www.ncbi.nlm.nih.gov/pubmed/33266961 http://dx.doi.org/10.3390/e21030247 |
Ejemplares similares
-
Compressive Sensing via Variational Bayesian Inference under Two Widely Used Priors: Modeling, Comparison and Discussion
por: Shekaramiz, Mohammad, et al.
Publicado: (2023) -
Exploration vs. Data Refinement via Multiple Mobile Sensors
por: Shekaramiz, Mohammad, et al.
Publicado: (2019) -
Compressed sensing & sparse filtering
por: Carmi, Avishy Y, et al.
Publicado: (2013) -
Compressed-Sensing Reconstruction Based on Block Sparse Bayesian Learning in Bearing-Condition Monitoring
por: Sun, Jiedi, et al.
Publicado: (2017) -
Sparse Reconstruction of Sound Field Using Bayesian Compressive Sensing and Equivalent Source Method
por: Xiao, Yue, et al.
Publicado: (2023)