Sparse Decomposition (SD) of a signal on an overcomplete dictionary has recently attracted a lot of interest in signal processing and statistics, because of its potential applicat...
Massoud Babaie-Zadeh, Vincent Vigneron, Christian ...
Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as 1-minimization find the sparse...
A significant Fourier transform (SFT) algorithm, given a threshold and oracle access to a function f, outputs (the frequencies and approximate values of) all the -significant Fou...
This paper explores the applicability of new sparse algorithms to perform spectral unmixing of hyperspectral images using available spectral libraries instead of resorting to well...
Marian-Daniel Iordache, Antonio J. Plaza, Jos&eacu...
A novel STAP algorithm based on sparse recovery technique, called CS-STAP, were presented. Instead of using conventional maximum likelihood estimation of covariance matrix, our met...
Ke Sun, Hao Zhang, Gang Li, Huadong Meng, Xiqin Wa...