对最佳采样的追求：压缩传感的计算效率，结构开发测量
The quest for optimal sampling: Computationally efficient, structure-exploiting measurements for compressed sensing
摘要：
在压缩感知的许多实例中，一个有趣的现象是，重建质量不仅取决于信号的整体稀疏性，还取决于其结构。本文是关于理解这种现象，并演示如何可以有效地利用它的设计合适的采样策略，以优于更标准的压缩感知技术的基础上随机矩阵。
英文摘要：
An intriguing phenomenon in many instances of compressed sensing is that the reconstruction quality is governed not just by the overall sparsity of the signal, but also on its structure. This paper is about understanding this phenomenon, and demonstrating how it can be fruitfully exploited by the design of suitable sampling strategies in order to outperform more standard compressed sensing techniques based on random matrices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
