CAREER: Acquisition, Approximation, and Compression - An Integrated Study

职业：采集、近似和压缩——一项综合研究

• 批准号: 0643836
• 负责人: Vivek Goyal
• 金额: $ 40万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-02-15 至 2012-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0643836&HistoricalAwards=false
• 关键词: CAREER; Acquisition; Approximation; Compression; Integrated

This project seeks to develop new algorithms for data acquisition that mitigate fundamental limitations in real-world measurement devices. All measurement devices are limited in their speed and timing accuracy. The corresponding primary goal is to develop algorithms to compensate for effects of timing inaccuracy and to extract information effectively from samples taken slowly. This could enable cheaper, smaller and lower-power measurement devices and thus hasten the deployment of large-scale and battery-operated sensing systems. Magnetic resonance imaging (MRI) systems are limited by the homogeneity of the induced magnetic excitation. A second project goal is to optimize excitation sequences for homogeneity without increase in excitation time. This would make ultra high-field MRI more useful clinically and in physiological research, with a significant impact on health care. Key to the technological advances is the careful integration of tools from approximation and compression into data acquisition. The research plan is complemented by the development of a textbook, a graduate course, and materials to be shared online at MIT Open Course Ware and FourierAndWavelets.org.The research has three parts: (a) Algorithms to mitigate jitter in sampled, quantized data will be developed. Since some power consumption is inversely proportional to the variance of jitter, these algorithmic improvements can enable lower power. The project further seeks to determine fundamental scaling laws for the effect of jitter. (b) The project addresses the estimation of signals from a small (sub-Nyquist) number of samples. Preliminary results demonstrate that approximation theory and information theory give quite different perspectives on the efficacy of existing techniques, and new acquisition and reconstruction algorithms will be developed. (c) MRI excitation design is posed as an approximation problem amenable to sparsity-based optimization

该项目旨在开发新的数据采集算法，以减轻现实世界测量设备的基本限制。 所有的测量设备在速度和定时精度上都是有限的。 相应的主要目标是开发算法来补偿定时不准确的影响，并从缓慢采集的样本中有效地提取信息。 这可以实现更便宜，更小和更低功耗的测量设备，从而加快大规模和电池供电传感系统的部署。 磁共振成像（MRI）系统受到感应磁激励的均匀性的限制。 第二个项目目标是优化激励序列的均匀性，而不增加激励时间。 这将使超高场MRI在临床和生理研究中更加有用，对医疗保健产生重大影响。 技术进步的关键是将近似和压缩工具仔细集成到数据采集中。 该研究计划的补充是开发一本教科书，一门研究生课程，以及在MIT Open Course Ware和FourierAndWavelet.org上在线共享的材料。该研究有三个部分：（a）将开发减轻采样量化数据抖动的算法。 由于某些功耗与抖动的方差成反比，因此这些算法改进可以实现更低的功耗。 该项目进一步寻求确定抖动效应的基本比例定律。 (b)该项目解决了从一个小的（子奈奎斯特）样本数量的信号估计。 初步结果表明，近似理论和信息论给出了相当不同的观点，现有技术的功效，新的采集和重建算法将被开发。(c)MRI激励设计是一个近似问题服从稀疏为基础的优化