43 citations · 162 across the 29 of their papers we have counts for
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cs.IT2014★ 5 cited
Reconstruction of Randomly Sampled Sparse Signals Using an Adaptive Gradient Algorithm
Ljubisa Stankovic, Milos Dakovic
Sparse signals can be recovered from a reduced set of samples by using compressive sensing algorithms. In common methods the signal is recovered in the sparse domain. A method for…
cs.IT2014★ 36 cited
Polynomial Fourier Domain as a Domain of Signal Sparsity
Srdjan Stankovic, Irena Orovic, Ljubisa Stankovic
A compressive sensing (CS) reconstruction method for polynomial phase signals is proposed in this paper. It relies on the Polynomial Fourier transform, which is used to establish a…
cs.IT2014★ 43 cited
On the ISAR Image Analysis and Recovery with Unavailable or Heavily Corrupted Data
Ljubisa Stankovic
Common ISAR radar images and signals can be reconstructed from much fewer samples than the sampling theorem requires since they are usually sparse. Unavailable randomly positioned…