论文标题
返回美国-SR：无限的采样和稀疏的超级分辨率，其硬件验证
Back in the US-SR: Unlimited Sampling and Sparse Super-Resolution with its Hardware Validation
论文作者
论文摘要
无限传感框架（USF）是一种数字采集协议，允许对高动态范围信号进行采样和重建。通过获取Modulo样品，USF避免了剪辑或饱和问题，这是常规类似物转换器（ADC）中基本瓶颈的剪裁或饱和问题。在USF的上下文中，几项工作重点介绍了限制功能类，最近，已经介绍了Modulo采样方法的硬件验证。在不同的方向上，在本文中，我们专注于非限制功能类别，并考虑众所周知的超分辨率问题。我们研究了低通滤波的模量样品的稀疏信号（狄拉克冲动）的回收。我们采用端到端的基于USF的超分辨率，提出了一种新型的恢复算法（US-SR），该算法利用了模量样品的双重稀疏结构。我们为US-SR方法得出一个采样标准。使用Modulo ADC进行的硬件实验证明了我们方法在现实，嘈杂的环境中的经验鲁棒性，从而验证了其实际效用。
The Unlimited Sensing Framework (USF) is a digital acquisition protocol that allows for sampling and reconstruction of high dynamic range signals. By acquiring modulo samples, the USF circumvents the clipping or saturation problem that is a fundamental bottleneck in conventional analog-to-digital converters (ADCs). In the context of the USF, several works have focused on bandlimited function classes and recently, a hardware validation of the modulo sampling approach has been presented. In a different direction, in this paper we focus on non-bandlimited function classes and consider the well-known super-resolution problem; we study the recovery of sparse signals (Dirac impulses) from low-pass filtered, modulo samples. Taking an end-to-end approach to USF based super-resolution, we present a novel recovery algorithm (US-SR) that leverages a doubly sparse structure of the modulo samples. We derive a sampling criterion for the US-SR method. A hardware experiment with the modulo ADC demonstrates the empirical robustness of our method in a realistic, noisy setting, thus validating its practical utility.
