Abstract

Heuristic search has recently been utilized for compressed sensing signal recovery problem by the A* Orthogonal Matching Pursuit (A*OMP) algorithm. A*OMP employs A* search on a tree with an OMP-based evaluation of the branches, where the search is terminated when the desired path length is achieved. The algorithm employs effective pruning techniques and cost models which make the tree search practical. Here, we propose two important extensions of A*OMP: We first introduce a novel dynamic cost model that reduces the search time. Second, we modify the termination criterion by stopping the search when l2 norm of the residue is small enough. Following the restricted isometry property, this termination criterion is more appropriate for our purposes. We demonstrate the improvements in terms of both reconstruction accuracy and computation times via a wide range of simulations.

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