The power of sparse signal coding with learned overcomplete dictionaries has been demonstrated in a variety of applications and fields, from signal processing to statistical infe...
Many backtracking algorithms exhibit heavy-tailed distributions, in which their running time is often much longer than their median. We analyze the behavior of two natural variant...
We consider the problem of estimating a deterministic sparse vector x0 from underdetermined measurements Ax0 +w, where w represents white Gaussian noise and A is a given determinis...
We study the distributed sampling and centralized reconstruction of two correlated signals, modeled as the input and output of an unknown sparse filtering operation. This is akin ...
Ali Hormati, Olivier Roy, Yue M. Lu, Martin Vetter...
Abstract—Compressive sampling (CS) has emerged as significant signal processing framework to acquire and reconstruct sparse signals at rates significantly below the Nyquist rate...