论克罗内克结构矩阵的限制等势特性

Yanbin He, Geethu Joseph
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引用次数: 0

摘要

在这项工作中,我们研究了由两个因子矩阵的克朗内克乘积形成的克朗内克结构矩阵的受限等几何性质(RIP)。在此之前,我们只知道以因子矩阵的 RIC 为单位的受限等势常数(RIC)的上下限。韦德提出了一个关于 $s$th-order RIC 的概率测量边界。我们证明,如果两个亚高斯矩阵的最小行数为 $\mathcal{O}(s\ln \max\{N_1,N_2\})$,则两个亚高斯矩阵的克朗内克乘以高概率满足 RIP。这里,$s$ 是稀疏程度,$N_1$ 和 $N_2$ 是矩阵的列数。我们还提出了使用 Kronecker 结构测量矩阵恢复 Kronecker 结构稀疏向量的改进测量边界。最后,我们的分析进一步扩展到两个以上矩阵的 Kronecker 乘积。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On the Restricted Isometry Property of Kronecker-structured Matrices
In this work, we study the restricted isometry property (RIP) of Kronecker-structured matrices, formed by the Kronecker product of two factor matrices. Previously, only upper and lower bounds on the restricted isometry constant (RIC) in terms of the RICs of the factor matrices were known. We derive a probabilistic measurement bound for the $s$th-order RIC. We show that the Kronecker product of two sub-Gaussian matrices satisfies RIP with high probability if the minimum number of rows among two matrices is $\mathcal{O}(s \ln \max\{N_1, N_2\})$. Here, $s$ is the sparsity level, and $N_1$ and $N_2$ are the number of columns in the matrices. We also present improved measurement bounds for the recovery of Kronecker-structured sparse vectors using Kronecker-structured measurement matrices. Finally, our analysis is further extended to the Kronecker product of more than two matrices.
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