PEAK CORRELATION AND CLUSTERING IN FLUIDIC SAMPLE SEPARATION
    1.
    发明申请
    PEAK CORRELATION AND CLUSTERING IN FLUIDIC SAMPLE SEPARATION 有权
    流体样品分离中的峰值相关性和聚类分析

    公开(公告)号:US20120116689A1

    公开(公告)日:2012-05-10

    申请号:US13252731

    申请日:2011-10-04

    CPC classification number: G06F19/707 G06F19/708 G06T11/206

    Abstract: A device (100) for analyzing measurement data having a plurality of data sets (206), each data set (206) being assigned to a respective one of a plurality of measurements, each data set (206) having multiple features (208) being indicative of different fractions of a fluidic sample, the device (100) comprising a cluster determining unit (108) configured for determining feature clusters (350) by clustering features (208) from different data sets (206) presumably relating to the same fraction, a spread determining unit (110) configured for determining for at least a part of the feature clusters (350) a spread (352) of the features (208) within a respective feature cluster (350), and a display unit (112) configured for displaying at least the part of the feature clusters (350) together with a graphical indication of the corresponding spread (352).

    Abstract translation: 一种用于分析具有多个数据集(206)的测量数据的装置(100),每个数据组(206)被分配给多个测量中的相应一个,每个数据组(206)具有多个特征(208) 指示流体样本的不同分数,所述设备(100)包括:群集确定单元(108),其被配置为通过从可能与相同分数相关的不同数据集(206)聚类特征(208)来确定特征群集(350) 扩展确定单元(110),被配置用于确定特征群集(350)的至少一部分(350)各个特征集群(350)内的特征(208)的扩展(352);以及配置 用于将特征簇(350)的至少一部分与对应扩展(352)的图形指示一起显示。

    Peak correlation and clustering in fluidic sample separation

    公开(公告)号:US09792416B2

    公开(公告)日:2017-10-17

    申请号:US13252731

    申请日:2011-10-04

    CPC classification number: G06F19/707 G06F19/708 G06T11/206

    Abstract: A device for analyzing measurement data having a plurality of data sets, each data set being assigned to a respective one of a plurality of measurements, each data set having multiple features being indicative of different fractions of a fluidic sample, the device comprising a cluster determining unit configured for determining feature clusters by clustering features from different data sets presumably relating to the same fraction, a spread determining unit configured for determining for at least a part of the feature clusters a spread of the features within a respective feature cluster, and a display unit configured for displaying at least the part of the feature clusters together with a graphical indication of the corresponding spread.

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