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    • 84. 发明授权
    • Method for identifying components of a mixture via spectral analysis
    • 通过光谱分析识别混合物的组分的方法
    • US07072770B1
    • 2006-07-04
    • US10812233
    • 2004-03-29
    • Robert SchweitzerWillem WindigPatrick J. Treado
    • Robert SchweitzerWillem WindigPatrick J. Treado
    • G01N31/00
    • G01J3/28G01N21/3577G01N21/359G01N33/02G01N2021/3129G01N2201/1293G06F19/703
    • The present invention is directed generally toward the field of spectral analysis and, more particularly, toward an improved method of identifying unknown components of a mixture from a set of spectra collected from the mixture using a spectral library including potential candidates. For example, the present method is directed to identifying components of a mixture by the steps which comprise obtaining a set of spectral data for the mixture that defines a mixture data space; ranking a plurality of library spectra of known elements according to their angle of projection into the mixture data space; calculating a corrected correlation coefficient for each combination of the top y ranked library spectra; and selecting the combination having the highest corrected correlation coefficient, wherein the known elements of the selected combination are identified as the components of the mixture.
    • 本发明一般涉及光谱分析领域,更具体地说,涉及使用包括潜在候选物的光谱库从混合物中收集的一组光谱识别混合物的未知组分的改进方法。 例如,本方法旨在通过包括获得用于限定混合数据空间的混合物的一组光谱数据的步骤来识别混合物的组分; 根据其投影到混合数据空间的角度对已知元素的多个库光谱进行排序; 计算顶级排名图书馆光谱的每个组合的校正相关系数; 以及选择具有最高校正相关系数的组合,其中所选组合的已知元素被识别为混合物的组分。
    • 88. 再颁专利
    • Spectroscopic imaging device employing imaging quality spectral filters
    • 使用成像质量光谱滤光片的光谱成像装置
    • USRE36529E
    • 2000-01-25
    • US996497
    • 1997-12-23
    • Edgar N. LewisIra W. LevinPatrick J. Treado
    • Edgar N. LewisIra W. LevinPatrick J. Treado
    • G01J3/28G02B21/33G01B9/02G01J3/44G01N21/35G01N21/64
    • G02B21/33G01J3/2823
    • Techniques for providing spectroscopic imaging integrates an acousto-optic tunable filter (AOTF), or an interferometer, and a focal plane array detector. In operation, wavelength selectivity is provided by the AOTF or the interferometer. A focal plane array detector is used as the imaging detector in both cases. Operation within the ultraviolet, visible, near-infrared (NIR) spectral regions, and into the infrared spectral region, is achieved. The techniques can be used in absorption spectroscopy and emission spectroscopy. Spectroscopic images with a spectral resolution of a few nanometers and a spatial resolution of about a micron, are collected rapidly using the AOTF. Higher spectral resolution images are recorded at lower speeds using the interferometer. The AOTF technique uses entirely solid-state components and requires no moving parts. Alternatively, the interferometer technique employs either a step-scan interferometer or a continuously modulated interferometer.
    • 用于提供光谱成像的技术集成了声光可调谐滤波器(AOTF)或干涉仪,以及焦平面阵列检测器。 在操作中,波长选择性由AOTF或干涉仪提供。 在这两种情况下,使用焦平面阵列检测器作为成像检测器。 实现了紫外线,可见光,近红外(NIR)光谱区域和红外光谱区域内的操作。 该技术可用于吸收光谱和发射光谱学。 使用AOTF快速收集具有几纳米的光谱分辨率和约一微米的空间分辨率的光谱图像。 使用干涉仪以更低的速度记录较高的光谱分辨率图像。 AOTF技术使用完全固态组件,不需要移动部件。 或者,干涉仪技术采用步进扫描干涉仪或连续调制干涉仪。
    • 89. 发明授权
    • Forensic integrated search technology with instrument weight factor determination
    • 法医综合检索技术与仪器重量因子测定
    • US08112248B2
    • 2012-02-07
    • US12017445
    • 2008-01-22
    • Robert SchweitzerPatrick J. TreadoJason Neiss
    • Robert SchweitzerPatrick J. TreadoJason Neiss
    • G06F17/18G01N31/00
    • G06K9/00536G06F19/703G06F19/709H01J49/0036
    • A system and method to search spectral databases and to identify unknown materials from multiple spectroscopic data in the databases. The methodology may be substantially automated and is configurable to determine weights to be accorded to spectroscopic data from different spectroscopic data generating instruments for improved identification of unknown materials. Library spectra from known materials are divided into training and validation sets. Initial, instrument-specific weighting factors are determined using a weight grid or weight scale. The training and validation spectra are weighted with the weighting factors and indicator probabilities for various sets of “coarse” weighting factors are determined through an iterative process. The finally-selected set of coarse weighting factors is further “fine tuned” using a weight grid with finer values of weights. The instrument-specific finer weight values may be applied to test data sets (or spectra) of an unknown material as well as to the library spectra from corresponding spectroscopic instruments. Instrument-specific weights for each class of samples may also be computed for additional customization and accuracy.
    • 一种用于搜索光谱数据库并从数据库中的多个光谱数据中识别未知物质的系统和方法。 该方法可以基本上是自动化的,并且可配置为确定要与来自不同光谱数据生成装置的光谱数据一致的权重,以改进未知材料的识别。 已知材料的谱图谱分为训练和验证集。 使用权重网格或权重量表确定初始的仪器特定加权因子。 训练和验证光谱通过加权因子加权,并且通过迭代过程确定各组“粗”加权因子的指标概率。 最终选择的粗加权系数集合使用具有更精确的权重值的权重网格进一步“精细调整”。 仪器特定的更精细的重量值可以应用于未知材料的测试数据集(或光谱)以及来自相应光谱仪的文库光谱。 也可以计算每类样品的仪器特定重量,以获得额外的定制和准确性。