Quantitative Recovery Conditions for Tree-Based Compressed Sensing
Quantitative Recovery Conditions for Tree-Based Compressed Sensing
As shown by Blumensath and Davies (2009) and Baraniuk et al. (2010), signals whose wavelet coefficients exhibit a rooted tree structure can be recovered using specially adapted compressed sensing algorithms from just n = O(k) measurements, where k is the sparsity of the signal. Motivated by these results, we introduce …