Compressed sensing algorithms for electromagnetic imaging applications
Compressed Sensing (CS) theory is a novel signal processing paradigm, which states that sparse signals of interest can be accurately recovered from a small set of linear measurements using efficient L1-norm minimization techniques. CS theory has been successfully applied to many sensing applications...
Published: |
|
---|---|
Online Access: | http://hdl.handle.net/2047/D20238457 |
Similar Items
-
Compressive sensing for electromagnetic imaging using a Nesterov-based algorithm
Published: () -
Matrix Element-Based Theory of Compressive Sensing and Its Application to Electromagnetic Imaging
by: Pratik Shah, et al.
Published: (2021-01-01) -
Compressed Sensing : Algorithms and Applications
by: Sundman, Dennis
Published: (2012) -
Compressive Sensing and Imaging Applications
Published: (2013) -
Novel forward–backward algorithms for optimization and applications to compressive sensing and image inpainting
by: Suthep Suantai, et al.
Published: (2021-05-01)