Cargando…
A Regularized Weighted Smoothed L(0) Norm Minimization Method for Underdetermined Blind Source Separation
Compressed sensing (CS) theory has attracted widespread attention in recent years and has been widely used in signal and image processing, such as underdetermined blind source separation (UBSS), magnetic resonance imaging (MRI), etc. As the main link of CS, the goal of sparse signal reconstruction i...
Autores principales: | Wang, Linyu, Yin, Xiangjun, Yue, Huihui, Xiang, Jianhong |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308515/ https://www.ncbi.nlm.nih.gov/pubmed/30518076 http://dx.doi.org/10.3390/s18124260 |
Ejemplares similares
-
Fault Feature Extraction for Reciprocating Compressors Based on Underdetermined Blind Source Separation
por: Wang, Jindong, et al.
Publicado: (2021) -
Underdetermined DOA Estimation for Wideband Signals via Focused Atomic Norm Minimization
por: Shi, Juan, et al.
Publicado: (2020) -
A Novel Underdetermined Blind Source Separation Method and Its Application to Source Contribution Quantitative Estimation
por: Lu, Jiantao, et al.
Publicado: (2019) -
Underdetermined Blind Source Separation with Variational Mode Decomposition for Compound Roller Bearing Fault Signals
por: Tang, Gang, et al.
Publicado: (2016) -
A Photoacoustic Imaging Algorithm Based on Regularized Smoothed L(0) Norm Minimization
por: Liu, Xueyan, et al.
Publicado: (2021)