Restricted p-isometry properties of nonconvex block-sparse compressed sensing ?
We establish a p-RIP condition for robust recovery of nearly block-sparse signals via mixed l2/lp-minimization. We obtain a stronger version p-RIP condition for exact recovery of block-sparse signals via mixed l2/lp-minimization. We determine how many random, Gaussian measurements are sufficient for the p-RIP condition to be satisfied with high probability. A series of numerical experiments have been carried out to prove the validation of our presented theoretical results.
restricted p-isometry properties compressed sensing mixed l2/lp-minimization gaussian measurements block-sparse signal recovery