Compressed sensing with applications in wireless networks
Sparsity is an attribute present in a myriad of natural signals and systems, occurring either inherently or after a suitable projection. Such […]
Signal Reconstruction of Compressed Sensing Based on Alternating Direction Method of Multipliers
The sparse signal reconstruction of compressive sensing can be accomplished by \(l_1\)-norm minimization, but in many existing algorithms, there are the problems […]
An Embedded Programmable Processor for Compressive Sensing Applications
An application specific programmable processor is designed based on the analysis of a set of greedy recovery Compressive Sensing (CS) algorithms. The […]