知识辅助的规范化迭代硬存储算法及其在稀疏重建中的应用
Knowledge-Aided Normalized Iterative Hard Thresholding Algorithms and Applications to Sparse Reconstruction
摘要：
本文讨论了利用先验知识的压缩感知应用中经常发现的稀疏恢复问题。特别是，我们提出了一个知识辅助归一化迭代硬阈值（KA-NIHT）算法，利用非零条目的概率信息。我们还开发了一种策略，使用递归KA-NIHT（RKA-NIHT）算法，从而提高恢复更新的概率。仿真结果表明，并比较所提出的算法和现有的性能。
英文摘要：
This paper deals with the problem of sparse recovery often found in compressive sensing applications exploiting a priori knowledge. In particular, we present a knowledge-aided normalized iterative hard thresholding (KA-NIHT) algorithm that exploits information about the probabilities of nonzero entries. We also develop a strategy to update the probabilities using a recursive KA-NIHT (RKA-NIHT) algorithm, which results in improved recovery. Simulation results illustrate and compare the performance of the proposed and existing algorithms.
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