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    • 21. 发明授权
    • Method and apparatus for spatio-temporal compressive sensing
    • 用于时空压缩感测的方法和装置
    • US08458109B2
    • 2013-06-04
    • US12787428
    • 2010-05-26
    • Yin ZhangLili Qiu
    • Yin ZhangLili Qiu
    • G06F17/00
    • G06K9/6232
    • A method and apparatus for spatio-temporal compressive sensing, which allows accurate reconstruction of missing values in any digital information represented in matrix or tensor form, is disclosed. The method of embodiments comprises three main components: (i) a method for finding sparse, low-rank approximations of the data of interest that account for spatial and temporal properties of the data, (ii) a method for finding a refined approximation that better satisfies the measurement constraints while staying close to the low-rank approximations obtained by SRMF, and (iii) a method for combining global and local interpolation. The approach of embodiments also provides methods to perform common data analysis tasks, such as tomography, prediction, and anomaly detection, in a unified fashion.
    • 公开了一种用于空间 - 时间压缩感测的方法和装置,其允许以矩阵或张量形式表示的任何数字信息中的缺失值的精确重建。 实施例的方法包括三个主要部分:(i)用于发现考虑到数据的空间和时间属性的感兴趣的数据的稀疏,低等级近似的方法,(ii)用于找到更好的精确近似的方法 满足测量约束,同时保持接近由SRMF获得的低阶近似,以及(iii)一种用于组合全局和局部插值的方法。 实施例的方法还提供了以统一的方式执行诸如断层摄影,预测和异常检测的共同数据分析任务的方法。
    • 27. 发明申请
    • METHOD AND APPARATUS FOR SPATIO-TEMPORAL COMPRESSIVE SENSING
    • 用于空间压缩感测的方法和装置
    • US20100306290A1
    • 2010-12-02
    • US12787428
    • 2010-05-26
    • Yin ZhangLili Qiu
    • Yin ZhangLili Qiu
    • G06F17/17G06F17/11G06F7/00
    • G06K9/6232
    • A method and apparatus for spatio-temporal compressive sensing, which allows accurate reconstruction of missing values in any digital information represented in matrix or tensor form, is disclosed. The method of embodiments comprises three main components: (i) a method for finding sparse, low-rank approximations of the data of interest that account for spatial and temporal properties of the data, (ii) a method for finding a refined approximation that better satisfies the measurement constraints while staying close to the low-rank approximations obtained by SRMF, and (iii) a method for combining global and local interpolation. The approach of embodiments also provides methods to perform common data analysis tasks, such as tomography, prediction, and anomaly detection, in a unified fashion.
    • 公开了一种用于空间 - 时间压缩感测的方法和装置,其允许以矩阵或张量形式表示的任何数字信息中的缺失值的精确重建。 实施例的方法包括三个主要部分:(i)用于发现考虑到数据的空间和时间属性的感兴趣的数据的稀疏,低等级近似的方法,(ii)用于找到更好的精确近似的方法 满足测量约束,同时保持接近由SRMF获得的低阶近似,以及(iii)一种用于组合全局和局部插值的方法。 实施例的方法还提供了以统一的方式执行诸如断层摄影,预测和异常检测的共同数据分析任务的方法。