Bio-inspired Fiber-Optics System based on Crayfish Escape Response for Ultrafast Adaptive Sensing

传感器系统面临着巨大的传输带宽、能量和数据存储限制，这是由于在动态环境中保持感知准确性所需的大量资源造成的。当传感器高度移动或传感器位置处于敌对状态时，这种情况会加剧，因为手动重新配置传感器以适应环境中的任何动态非常困难。当前的传感器设计要么是非自适应的，要么需要大量的存储资源，因此，只有一小部分数据以足够的质量水平被传送到对应用有用的水平。如果传感器系统可以智能地适应快速变化的环境，则可以使用来自先前收集的数据的信息来即时指导传感器配置和数据选择，而不需要离线存储和处理数据。该项目是一种受神经启发的新方法，能够实现实时自适应感知，从而提高传感器系统的整体带宽利用率、功率效率和传感器精度。准确的实时自适应感知可以显著减少自然灾害和人为灾害造成的财产损失。它还可以通过识别故意的恐怖行动来提高国家安全，以及为安全应用提供智能实时大带宽自适应传感系统。这项工作的教育影响来自于它的多学科基础，开阔了学生的视野，鼓励他们跳出框框思考。本项目借鉴了生理电路中的小龙虾翻尾逃逸反应和脉冲定时相关可塑性，旨在用光子学来实现它。本项目的重点是设计和开发一种能够实时学习和适应快速变化的光子神经小龙虾电路，并将用于实时自适应控制的光子小龙虾电路集成到传感器系统中。这项倡议是一项跨学科的综合设备和系统设计研究，涉及从神经形态处理的角度进行基础研究。该项目旨在利用光子器件中的物理过程，并解决动态和复杂的现代传感器系统中的基本实时自适应控制问题。这种全新的方法是一种受神经启发的方法，通过消除计算瓶颈并提供实时自适应感知所需的高保真和大带宽处理能力来解决问题。

Sensor systems are facing significant transmission bandwidth, energy, and data storage constraints caused by the vast amount of resources needed to maintain sensing accuracy in a dynamic environment. This situation is exacerbated when the sensor is highly mobile or when the sensor site is hostile, as it is very difficult to manually reconfigure a sensor to accommodate any dynamics in the environment. Current sensor designs are either non-adaptive or require large storage resources and, as a result, only a small fraction of the data be conveyed at a sufficient quality level to be useful for applications. If it is possible for the sensor system to intelligently adapt to the rapidly changing environment, then information from previously collected data can be used to instantaneously guide sensor configuration and the selection of data without the need to store and process the data offline. This project is a new neural-inspired approach to enable real-time adaptive sensing, such that the overall bandwidth usage, power efficiency, and sensor accuracy of the sensor system will be improved. Accurate real-time adaptive sensing can significantly reduce property damage due to natural and manmade disasters. It can also improve national security by identifying intentional terrorist actions, as well as providing an intelligent real-time large bandwidth adaptive sensing system for security applications. The educational impact of this work comes from its multi-disciplinary foundation, broadening students' views and encouraging them to think outside the box.This project borrows the Crayfish Tail-flip Escape Response and the Spike Timing Dependent Plasticity from physiological circuitry, and aims to implement it with photonics. The focus of this project is to design and develop a photonic neural crayfish circuit, capable of real-time learning and adapting to rapid changes, and to incorporate the photonic crayfish circuit for real-time adaptive control in a sensor system. This initiative is an interdisciplinary integrated device and systems design study involving basic research from the standpoint of neuromorphic processing. The project aims to exploit physical processes in photonic devices, and to solve the problem of fundamental real-time adaptive control in a dynamic and complex modern sensor system. This fundamentally novel approach is a neural-inspired way to solve the problem by eliminating the computing bottleneck and providing high fidelities and large bandwidth processing ability that is needed for real-time adaptive sensing.