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Multi-Sparse Signal Recovery for Compressive Sensing
Multi-Sparse Signal Recovery Compressive Sensing Information Theory
2012/6/19
Signal recovery is one of the key techniques of Compressive sensing (CS). It reconstructs the original signal from the linear sub-Nyquist measurements. Classical methods exploit the sparsity in one do...
In this paper, we demonstrate some applications of compressive sensing over networks. We make a connection between compressive sensing and traditional information theoretic techniques in source coding...
The problem of compressing a real-valued sparse source using compressive sensing techniques is studied. The rate distortion optimality of a coding scheme in which compressively sensed signals are qua...
Restricted p-isometry property and its application for nonconvex compressive sensing
Compressed sensing lp minimization instance optimality stability
2018/4/19
Compressed sensing is a new scheme which shows the ability to recover sparse signal from fewer measurements, using l1 minimization. Recently, Chartrand and Staneva shown in [7] that the lp minimizatio...