Collaborative Research: ATD: Dynamical sampling and reconstruction for sensing networks of physical fields

PI开发和测试用于新的采样和重建框架的理论和算法，该框架将初始状态的空间样本与演化状态的早期时间样本相结合，以重建初始分布和可能未知的演化算子。利用信号的进化特性，PI旨在从在适当的时间间隔获得的多个粗略快照中以精细分辨率恢复初始分布。拟议研究的最重要方面之一是提供使用分布式传感器网络(如人们携带的智能手机)检测潜在社会威胁(如化学、核或生物危害)的方法，快速收集和处理有关威胁来源位置及其分布和随时间演变的信息，并生成警报，以便采取适当措施保护生命和基础设施。同样的想法也可以用于其他工业或生物医学应用中，其中样品之间的时间依赖性允许通过增加昂贵仪器的使用频率来减少其数量。

The PIs develop and test the theory and algorithms for a new sampling and reconstruction framework that combines spatial samples of an initial state together with the early time samples of an evolving state to reconstruct the initial distribution and the possibly unknown evolution operator. Using the evolutionary nature of a signal, the PIs aim to recover an initial distribution at a fine resolution from multiple coarse snapshots obtained at appropriate time intervals.One of the most important aspects of the proposed research is to provide the means to detect potential threats to society (such as chemical, nuclear or biological hazards) using a network of distributed sensors such as the smartphones people carry, rapidly gather and process the information about the threats source location and its distribution and evolution in time, and generate alerts so that appropriate measures are taken to safeguard life and infrastructure. The same ideas can be used in other industrial or biomedical applications in which the time-dependency between samples permits reduction in the number of expensive instruments via the increase of their usage frequency.