稀疏相位检索通过最小化l_p (0 p≤1)

Int. J. Wavelets Multiresolution Inf. Process. Pub Date : 2021-07-05 DOI:10.1142/S021969132150034X

Manxia Cao, Wei Huang

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摘要

本文将冗余字典中稀疏未知信号相位检索问题的[公式:见文]-分析模型扩展为[公式:见文]-分析模型，其中[公式:见文]。结果表明，当测量矩阵[公式:见文]满足适应于D (S-DRIP)条件的强限制等距特性时，通过分析[公式:见文][公式:见文]最小化模型，可以稳定地恢复未知信号[公式:见文]。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Sparse phase retrieval via ℓp (0 p ≤ 1) minimization

In this paper, the [Formula: see text]-analysis model for the phase retrieval problem of sparse unknown signals in the redundant dictionary is extended to the [Formula: see text]-analysis model, where [Formula: see text]. It’s shown that if the measurement matrix [Formula: see text] satisfies the strong restricted isometry property adapted to D (S-DRIP) condition, the unknown signal [Formula: see text] can be stably recovered by analyzing the [Formula: see text] [Formula: see text] minimization model.

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Int. J. Wavelets Multiresolution Inf. Process.

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