An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery

An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery

Blog Article

Joint sparse recovery (JSR) in compressed sensing simultaneously recovers sparse signals with a common sparsity structure from their multiple measurement vectors obtained through a common sensing matrix.In this paper, we present Salt Lamps an Armijo-type hard thresholding (AHT) algorithm for joint sparse recovery.Under the restricted isometry property (RIP), Guard we show that the AHT can converge to a local minimizer of the optimization problem for JSR.Furthermore, we compute the AHT convergence rate with the above conditions.Numerical experiments show the good performance of the new algorithm for JSR.