Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as 1-minimization find the sparse...
We consider signals and operators in finite dimension which have sparse time-frequency representations. As main result we show that an S-sparse Gabor representation in Cn with re...
Abstract-- We consider lossy compression of a binary symmetric source by means of a low-density generator-matrix code. We derive two lower bounds on the rate distortion function wh...
Real-time high-definition video encoding is a computationhungry task that challenges software-based solutions. For that, in this work we adopted an Intel software implementation o...
Tiago A. da Fonseca, Ricardo L. de Queiroz, Debarg...
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...