An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery

An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery

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Joint sparse recovery (JSR) in compressed sensing simultaneously recovers sparse signals with a common hbl5266ca sparsity structure from their multiple measurement vectors obtained through a common sensing matrix.In this paper, we present an Armijo-type hard thresholding (AHT) algorithm for joint sparse recovery.Under the restricted isometry property click here (RIP), 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.