SHF: Small: Collaborative Research: CONTINUOUS-TIME DIGITAL COMPUTATION AND SIGNAL PROCESSING

本研究的目标是开发高性能和节能的数字信号处理器，使用一种新颖的事件驱动方法，包括仔细跟踪事件时间的特殊技术。与标准的“异步”逻辑不同，这种方法本质上使用物理时间作为其信息表示的一部分。在这项研究过程中开发的系统和技术可以使许多重要的应用受益，包括传感器网络和医疗保健中的生物医学仪器。所创造的知识体系也可能在其他领域得到应用，包括控制系统和机器人技术。这项工作具有重要的教育成分，因为它涉及协同发展，结合不同领域的知识，从而培养研究生和本科生参与跨学科工作，导致新的，创造性的解决方案。与传统技术相比，这种方法的吸引人的技术特性包括没有混叠，更好的误差光谱特性以及对输入变化的更快响应。该方法适用于要求极低功耗的某些应用，特别是涉及便携性或难以访问位置的应用。虽然之前的工作集中在证明连续时间数字信号处理器的可行性，但这项新的工作集中在开发下一代系统和实现非常高性能上，需要新的原理和技术。该工作旨在通过降低有效采样率和改进输出重建，通过使用特殊编码技术来放松信号处理单元中的粒度要求，通过直接处理非均匀量化信号以及采用算法技术来提高连续时间数字信号处理器的性能；它还将连续时间数字技术扩展到一般科学计算。拟议的工作将两个具有互补专业知识的小组聚集在一起。哥伦比亚大学的研究小组专门研究混合信号电路，并展示了第一个连续时间数字信号处理器；康奈尔大学的研究小组致力于异步数字电子学，包括事件驱动处理器和异步数据流fpga。

The goal of this research is to develop high-performance and power-efficient digital signal processors, using a novel event-driven approach involving special techniques that carefully keep track of the timing of events. Unlike standard "asynchronous" logic this approach inherently uses physical time as part of its representation of information. The systems and techniques to be developed in course of this research can benefit a number of important applications, including sensor networks and biomedical instrumentation in health care. The body of knowledge to be created would potentially find applications in other areas as well, including control systems and robotics. The work has a significant educational component, in that it involves synergistic development, combining different domains of knowledge and thus training the graduate and undergraduate students involved in interdisciplinary work, leading to new, creative solutions. Appealing technical properties of this approach include the absence of aliasing, better spectral properties of error, and faster response to changing inputs, compared to classical techniques. The approach is suitable for certain applications that demand very low power dissipation, notably those involving portability or difficult-to-access locations. While prior work concentrated on demonstrating the feasibility of continuous-time digital signal processors, this new effort concentrates on developing next-generation systems and achieving very high performance, necessitating new principles and techniques. The work seeks to advance the performance of continuous-time digital signal processors by reducing the effective sampling rate and improving output reconstruction, by using special coding techniques for relaxing granularity requirements in the signal processing units, by processing directly non-uniformly quantized signals, and by employing algorithmic techniques; it also expands continuous-time digital techniques to general scientific computation. The proposed effort brings together two groups with complementary expertise. The Columbia University group specializes in mixed-signal circuits and has demonstrated the first continuous-time digital signal processors; the Cornell University group works in asynchronous digital electronics, including event-driven processors and asynchronous dataflow FPGAs.