Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
This paper introduces a new algorithm for reconstructing signals with sparse spectrums from noisy compressive measurements. The proposed model-based algorithm takes the signal str...
We consider the problem of reconstructing time sequences of spatially sparse signals (with unknown and time-varying sparsity patterns) from a limited number of linear "incohe...
We consider the problem of recovering a target matrix that is a superposition of low-rank and sparse components, from a small set of linear measurements. This problem arises in co...
We propose a new method for imaging sound speed in breast tissue from measurements obtained by ultrasound tomography (UST) scanners. Given the measurements, our algorithm finds a...
Ivana Tosic, Ivana Jovanovic, Pascal Frossard, Mar...