课题基金 / 基金详情

A Scalable Configurable Acoustic Processor for Emerging Audio Applications

A Scalable Configurable Acoustic Processor for Emerging Audio Applications
适用于新兴音频应用的可扩展可配置声学处理器
批准号:
2153821
负责人:
Michael Flynn
金额:
$36.97万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-09-01 至 2025-08-31

项目摘要

项目成果

Michael Flynn的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Very large acoustic transducer arrays will transform how we sense, generate, and manipulate sound. However, existing acoustic processing systems are not able to support large arrays. This project tackles the challenges of scale, time accuracy, latency and synchronization in large acoustic arrays. The research of this project will free acoustic arrays from the electronic performance bottlenecks that impede large-scale operation. The new audio technologies involving large-scale electro-acoustic systems promise transformative acoustic applications and will have the potential to transform biology and medicine through contactless manipulation and surgery. For example, high-resolution acoustic holography promises contactless manipulation of biological specimens, non-invasive surgery, and new modes for augmented reality. By providing detailed soundscapes, large sensitive arrays allow new levels of environmental and industrial monitoring. For example, high precision acoustic imaging can locate wildlife, pinpoint machine faults, and identify noise from wind turbines. In addition, active metamaterials will enable the construction and control of soundscapes. These materials can manage the sound environment in weight-sensitive aerospace applications and provide health benefits by targeting the sound debris that litters urban environments. For example, large active metamaterial surfaces can quieten aircraft cabins or even enable acoustic invisibility. The project will introduce sound processing in the undergraduate circuits curriculum and use sounds, instead of optics and electromagnetics, to provide an intuitive understanding of challenging applied physics concepts such as holography and metamaterials. This research will provide rewarding and meaningful research opportunities for undergraduate and high-school students. This project will tackle scale, time, and signal-to-noise ratio (SNR) challenges of emerging acoustic applications and transform audio processing with new mixed-signal circuit techniques that deliver unprecedented spatial resolution, temporal resolution, and dynamic range for emerging acoustic applications. The scale, which corresponds to the number of transducers, ultimately determines the resolution and the SNR. Furthermore, practical applications such as acoustic metamaterials work best on a large scale. Another challenge for large arrays is temporal accuracy through phase control and precise time synchronization. The research will investigate new techniques to address the critical scale, time resolution, and latency problems that impede large-scale acoustic holography, acoustic imaging, and active acoustic metamaterials. In addition, the research will address issues of synchronization and distributed processing for large-scale arrayed systems. The new techniques will enable large-scale high-fidelity systems with unprecedented time accuracy, time control, and low latency. The project will use testbed systems to showcase the potential of the new techniques. Finally, the research will explore the potential tradeoffs of configurable mixed-signal processing of bitstream.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
NCS-FO: Collaborative Research: A Neurally-Inspired, Event-Based Computer Vision Pipeline
Fostering Dakota Language Restoration through Workshops: First Steps to Partnering by the Sisseton-Wahpeton Oyate, the Dakotah Language Institute and Carleton College
  • 批准号:
    1641556
  • 项目类别:
    Standard Grant
  • 资助金额:
    $1.89万
  • 财政年份:
    2016
  • 负责人:
    Michael Flynn
  • 依托单位:
CCF: Small: Smart Continually-aware High-Fidelity Sensor Interfaces
CIF: Small: Self-Synthesizing Mixed-signal Circuits
海外基金