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Recovery of Sparse 1-D Signals from the Magnitudes of their Fourier Transform
Recovery of Sparse 1-D Signals the Magnitudes their Fourier Transform Information Theory
2012/6/27
The problem of signal recovery from the autocorrelation, or equivalently, the magnitudes of the Fourier transform, is of paramount importance in various fields of engineering. In this work, for one-di...
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...
Sparse approximation property and stable recovery of sparse signals from noisy measurements
Sparse approximation property noisy measurements Information Theory
2011/9/21
Abstract: In this paper, we introduce a sparse approximation property of order $s$ for a measurement matrix ${\bf A}$: $$\|{\bf x}_s\|_2\le D \|{\bf A}{\bf x}\|_2+ \beta \frac{\sigma_s({\bf x})}{\sqrt...