
The Subspace Phase Retrieval (SPR) algorithm can accurately recover an n-dimensional k-sparse complex-valued signal from Ω(k log n) magnitude-only Gaussian samples, attaining the information-theoretic sampling complexity for sparse phase retrieval.


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efficient-sparse-phase-retrieval-algorithm-with-optimal-sampling-complexity


Efficient Sparse Phase Retrieval Algorithm with Optimal Sampling Complexity


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This paper proposes two fundamental improvements to the classical Orthogonal Matching Pursuit (OMP) algorithm to make it computationally more efficient while preserving its excellent performance guarantees. The proposed algorithms, OMP-SR and BSR, achieve significant speedup over OMP by avoiding the expensive computation of pseudo-inverse over an increasing-sized matrix.


fast-orthogonal-matching-pursuit-algorithm-for-exact-recovery-and-sparse-approximation


Fast Orthogonal Matching Pursuit Algorithm for Exact Recovery and Sparse Approximation
