A joint recovery algorithm for distributed compressed sensing

Distributed compressed sensing exploits the correlation among multiple signals to reduce the number of measurements required for recovery. In this paper, we propose a recovery algorithm for a type of joint sparsity model, where all signals share a common sparse component and each individual signal c