一种自适应的拟牛顿投影稀疏信号恢复算法

doi:10.19665/j.issn1001-2400.2019.03.003

摘要/Abstract

摘要：

针对稀疏恢复中贪婪类算法需要提前已知稀疏度的问题,提出了一种自适应拟牛顿投影稀疏恢复算法。该算法分为两层循环:外层循环主要是利用阈值算子估计信号的稀疏度,内层循环在外层迭代估计的当前稀疏度下,基于拟牛顿投影算法完成稀疏信号恢复。仿真实验表明:该方法相对于需要事先已知稀疏度的贪婪算法,可在稀疏度未知的情况下获得稀疏信号的较优逼近性与恢复率。

关键词: 稀疏恢复, 压缩感知, 自适应, 拟牛顿, 投影

Abstract:

An adaptive quasi-Newton projection sparse restoration algorithm is proposed to solve the problem that greedy algorithms need to know the sparsity in advance. The algorithm consists of two layers: the sparsity of the signal is estimated by using the threshold operator in the outer loop, and the sparse signal is recovered based on the quasi-Newton projection algorithm under the current sparsity of the outer iterative estimation in the inner loop. Simulation results show that this method has a better approximation performance and recovery rate of sparse signals with unknown sparsity compared with the greedy algorithms with known sparsity in advance.

Key words: sparse recovery, compressed sensing, adaptive, quasi-Newton, projection

中图分类号:

TN919.6

周雪芹,冯象初,景明利. 一种自适应的拟牛顿投影稀疏信号恢复算法[J]. 西安电子科技大学学报, 2019, 46(3): 14-19.

ZHOU Xueqin,FENG Xiangchu,JING Mingli. Adaptive quasi-newton projection algorithm for sparse recovery[J]. Journal of Xidian University, 2019, 46(3): 14-19.

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