On Compressed Sensing Matrices Breaking the Square-Root Bottleneck
On Compressed Sensing Matrices Breaking the Square-Root Bottleneck
Compressed sensing is a celebrated framework in signal processing and has many practical applications. One of the challenging problems in compressed sensing is to construct deterministic matrices having the restricted isometry property (RIP). So far, there are only a few publications providing deterministic RIP matrices beating the square-root bottleneck on …