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    • 7. 发明申请
    • Method and apparatus for analyzing multi-channel chromatogram
    • 用于分析多通道色谱图的方法和装置
    • US20060271310A1
    • 2006-11-30
    • US11501750
    • 2006-08-10
    • Masahito ItoKisaburo Deguchi
    • Masahito ItoKisaburo Deguchi
    • G01N31/00
    • G01N30/8624G01N30/8631G01N30/8679G01N2201/1293
    • A method for analyzing a multi-channel chromatogram is realized for accurately resolving overlapping peaks on a multi-channel chromatogram to permit analysis of the composition of a sample. First, components of overlapping peaks are specified. A data matrix Dij is determined, and compressed in the wavelength direction to obtain a data matrix vector Di. Next, the two-dimensional data is deconvoluted, final standard deviation s0 is registered, and the deconvoluted two-dimensional data is reconvoluted to a retention intensity matrix. A quantitative spectral intensity matrix is computed, components are identified, and the identified components are quantified. Subsequently, an eigenvalue problem is solved, and the number n of components is estimated. The deconvolution and computation of the eigenvalue problem are iteratively executed until the peaks are isolated. Then, elution profiles are calculated, the components are identified, and the identified components are quantified.
    • 实现了分析多通道色谱图的方法,用于准确地分辨多通道色谱图上的重叠峰,以便分析样品的组成。 首先,指定重叠峰的分量。 确定数据矩阵Dij,并在波长方向上压缩以获得数据矩阵向量Di。 接下来,对二维数据进行解卷积,记录最终标准偏差s0,并将解卷积的二维数据重新卷积到保留强度矩阵。 计算定量光谱强度矩阵,识别组件,并对所识别的组分进行量化。 随后,解决了特征值问题,并且估计了分量的数量n。 迭代执行反褶积和特征值问题的计算,直到峰被隔离。 然后,计算洗脱曲线,识别组分,并对所鉴定的组分进行定量。
    • 8. 发明授权
    • Method and apparatus for analyzing multi-channel chromatogram
    • US06393368B1
    • 2002-05-21
    • US08811486
    • 1997-03-05
    • Masahito ItoKisaburo Deguchi
    • Masahito ItoKisaburo Deguchi
    • G01N3000
    • G01N30/8624G01N30/8631G01N30/8679G01N2201/1293
    • A method for analyzing a multichannel chromatogram is realized for accurately resolving overlapping peaks on a multichannel chromatogram to permit analysis of the composition of a sample. First, components of overlapping peaks are specified. A data matrix Dij is determined, and compressed in the wavelength direction to obtain a data matrix vector Di. By compressing three-dimensional data in the wavelength direction, noise components cancel with each other to obtain noise free two-dimensional data Di&bgr;. Next, the two-dimensional data is deconvoluted, final standard deviation s0 is registered, and the deconvoluted two-dimensional data is reconvoluted to a retention intensity matrix. A quantitative spectral intensity matrix is computed, components are identified, and the identified components are quantified. The quantified data is displayed on a screen. Since noise components cancel with each other, it is possible to realize an analyzing method which is capable of accurately resolving and analyzing the components. Also, overlapping peaks are specified, and a data matrix D is determined. Subsequently, an eigenvalue problem is solved, and the number n of components is estimated. The deconvolution and computation of the eigenvalue problem are iteratively executed until the peaks are isolated. Then, elution profiles are calculated, the components are identified, and the identified components are quantified.
    • 10. 发明授权
    • Methods and apparatuses for analyzing multichannel chromatogram
    • 分析多通道色谱图的方法和装置
    • US5644503A
    • 1997-07-01
    • US409986
    • 1995-03-24
    • Masahito ItoKisaburo Deguchi
    • Masahito ItoKisaburo Deguchi
    • G01N27/447G01N30/86G01N31/00G01N30/00G06F17/16
    • G01N30/8624G01N2201/1293G01N30/8631G01N30/8679
    • A method for analyzing a multichannel chromatogram is realized for accurately resolving overlapping peaks on a multichannel chromatogram to permit analysis of the composition of a sample. First, components of overlapping peaks are specified. A data matrix Dij is determined, and compressed in the wavelength direction to obtain a data matrix vector Di. By compressing three-dimensional data in the wavelength direction, noise components cancel with each other to obtain noise free two-dimensional data Di.beta.. Next, the two-dimensional data is deconvoluted, final standard deviation s0 is registered, and the deconvoluted two-dimensional data is reconvoluted to a retention intensity matrix. A quantitative spectral intensity matrix is computed, components are identified, and the identified components are quantified. The quantified data is displayed on a screen. Since noise components cancel with each other, it is possible to realize an analyzing method which is capable of accurately resolving and analyzing the components. Also, overlapping peaks are specified, and a data matrix D is determined. Subsequently, an eigenvalue problem is solved, and the number n of components is estimated. The deconvolution and computation of the eigenvalue problem are iteratively executed until the peaks are isolated. Then, elution profiles are calculated, the components are identified, and the identified components are quantified.
    • 实现了用于分析多通道色谱图的方法,用于准确地分辨多通道色谱图上的重叠峰,以允许分析样品的组成。 首先,指定重叠峰的分量。 确定数据矩阵Dij,并在波长方向上压缩以获得数据矩阵向量Di。 通过在波长方向压缩三维数据,噪声分量彼此抵消,以获得无噪声的二维数据Diβ。 接下来,对二维数据进行解卷积,记录最终标准偏差s0,并将解卷积的二维数据重新卷积到保留强度矩阵。 计算定量光谱强度矩阵,识别组件,并对所识别的组分进行量化。 量化的数据显示在屏幕上。 由于噪声分量彼此抵消,因此可以实现能够精确地分析和分析组件的分析方法。 此外,指定重叠的峰值,并且确定数据矩阵D. 随后,解决了特征值问题,估计了组件的数量+ E,uns n + EE。 迭代执行反褶积和特征值问题的计算,直到峰被隔离。 然后,计算洗脱曲线,识别组分,并对所鉴定的组分进行定量。