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CAREER: A Generalized Compressive Sensing Approach to Data Acquisition and Ad-Hoc Sensor Networking

CAREER: A Generalized Compressive Sensing Approach to Data Acquisition and Ad-Hoc Sensor Networking
职业:数据采集和自组织传感器网络的通用压缩传感方法
批准号:
1056065
负责人:
Nazanin Rahnavard
金额:
$40.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-02-01 至 2014-02-28

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中文摘要
翻译
该项目的目标是通过利用特定问题的信号和系统特性来显著提高效率,从而推进压缩传感领域,并将其范围扩大到多种新的应用,如特设联网。提出的方法是设计一种新的无码率编码启发的广义压缩感知(GCS)框架,并将其集成到网络设计过程中的感知、信息处理和跨层设计的不同阶段。GCS允许灵活地利用特定于问题的属性,例如在感知和恢复阶段数据的非一致稀疏性和非一致重要性。预计这将大大降低传感和通信成本。通过GCS和底层网络协议的跨层设计,研究传感器网络中高效的数据获取和分布式数据存储问题。广泛的影响:这一建议有望对推动压缩感知的理论和实践产生重大的直接影响,并间接影响许多具有潜在应用前景的领域,如医学成像、高光谱成像和生物信息学。此外,它预计将在以下方面产生影响:让更多人数不足的学生参与国际和平研究所的研究小组,促进高中生的工程教育,通过课程编制/修订将研究与教育结合起来,培训研究生,以及通过在俄亥俄州立大学发起欧洲经委会研讨会日方案,促进多学科研究与合作。
英文摘要
The objective of this project is to advance the field of compressive sensing and broaden its scope into a multitude of new applications, such as ad hoc networking, by significantly enhancing the efficiency through the utilization of problem-specific signals and systems properties. The proposed approach is to design a novel rateless-coding-inspired generalized compressive sensing (GCS) framework and to integrate it into different stages of sensing, information processing, and cross-layer designs in the network design processes.Intellectual Merit: The proposed research bridges the gap between the advanced theoretical research on modern coding and compressive sensing, as to significantly enhance the efficiency of data acquisition and ad hoc networking. GCS offers the flexibility of exploiting problem-specific properties, such as non-uniform sparsity and non-uniform importance of data in the sensing and recovery phases. This is expected to result in a significant reduction in sensing and communication costs. Through cross-layer design of GCS and underlying network protocols, efficient data acquisition and distributed data storage problems in sensor networks will be investigated.Broader Impacts: This proposal is expected to have a significant direct impact on advancing the theory and practice of compressive sensing and an indirect impact on many areas in which compressive sensing has potential application, such as medical imaging, hyper-spectral imaging, and bio-informatics. Furthermore, it expected to have an impact on increasing the participation of under-represented students in the PI's research group, as well as in promoting engineering education among high school students, in integration of research and education through curriculum development/revision, in training graduate students, and in promoting multidisciplinary research and collaboration through initiating ECE Seminar Day Program at OSU.
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会议论文
Cross-layer Adaptive Rate/Resolution Design for Energy-Aware Acquisition of Spectrally Sparse Signals Leveraging Spin-based Devices
CIF:Small: A Tensor-based Framework for Reliable Radio Cartography
CAREER: A Generalized Compressive Sensing Approach to Data Acquisition and Ad-Hoc Sensor Networking
CIF: Small: Collaborative Research: Cooperative Sensing and Communications for Cognitive Radio Networks
国内基金
海外基金
三维流形的Generalized Seifert Fiber分解
  • 批准号:
    11526046
  • 项目类别:
    数学天元基金项目
  • 资助金额:
    3.0万元
  • 批准年份:
    2015
  • 负责人:
    王栋诩
  • 依托单位: