[HTML][HTML] DOTnet 2.0: Deep learning network for diffuse optical tomography image reconstruction
Breast cancer is the most common cancer worldwide. The standard imaging modality for
breast cancer screening is X-ray mammography, which suffers from low sensitivities in …
breast cancer screening is X-ray mammography, which suffers from low sensitivities in …
[PDF][PDF] Stochastic greedy algorithms for multiple measurement vectors
Sparse representation of a single measurement vector (SMV) has been explored in a variety
of compressive sensing applications. Recently, SMV models have been extended to solve …
of compressive sensing applications. Recently, SMV models have been extended to solve …
Stochastic greedy algorithms for multiple measurement vectors
Sparse representation of a single measurement vector (SMV) has been explored in a variety
of compressive sensing applications. Recently, SMV models have been extended to solve …
of compressive sensing applications. Recently, SMV models have been extended to solve …
Iterative singular tube hard thresholding algorithms for tensor recovery
Due to the explosive growth of large-scale data sets, tensors have been a vital tool to
analyze and process high-dimensional data. Different from the matrix case, tensor …
analyze and process high-dimensional data. Different from the matrix case, tensor …
Jointly sparse signal recovery with prior info
The multiple measurement vector (MMV) problem with jointly sparse signals has been of
recent interest across many fields and can be solved via ℓ 2, 1 minimization. In such …
recent interest across many fields and can be solved via ℓ 2, 1 minimization. In such …
A Simple Recovery Framework for Signals with Time-Varying Sparse Support
Sparse recovery methods have been developed to solve multiple measurement vector
(MMV) problems. These methods seek to reconstruct a collection of sparse signals from a …
(MMV) problems. These methods seek to reconstruct a collection of sparse signals from a …
[图书][B] Optimization for High-Dimensional Analysis and Estimation in Signal Processing and Machine Learning
S Li - 2020 - search.proquest.com
High-dimensional signal analysis and estimation appears in many signal processing and
machine learning applications, including modal analysis, airborne radar system demixing …
machine learning applications, including modal analysis, airborne radar system demixing …