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    • 5. 发明申请
    • METHOD FOR COMPUTER-ASSISTED EXTRACTION OF STATISTICALLY INDEPENDENT DIGITAL SIGNALS FROM DIGITAL SIGNALS
    • 方法计算机辅助提取统计独立的数字信号从数字输入信号
    • WO98041928A1
    • 1998-09-24
    • PCT/DE1998/000209
    • 1998-01-23
    • G06F17/18G06F17/40H04R3/00G06F17/00
    • G06K9/6242H04R3/005H04R2201/403
    • The invention relates to a method for extracting statistically independent signals from a mass of mixed input signals, based on the information maximization principle. Numerical stability of a method based on the information maximization principle is guaranteed when the determinants of the transformation matrix have a constant value (step 504) in the rule determining maximum likelihood expectation. The transformation matrix and likelihood expectation models of intermediate signals are adapted in a training phase (step 502). The statistically independent intermediate signals are determined (step 505) in relation to the input signals in an application phase using the transformation matrix arising after adaptation.
    • 所以建议从基于信息最大化的原理的量混合的输入信号为统计上独立的信号的提取的处理。 第一时间是基于信息最大化的,在所述过程的原理的过程的数值稳定性确保用于确定所述最大似然期望,变换矩阵的行列式具有恒定值(步骤504)。 变换矩阵以及中间信号的概率密度的模型是在训练阶段适于(步骤502)。 在一种应用相的输入信号,使用被适配后获得的变换矩阵中,在统计上独立的中间信号被确定(步骤505)。
    • 6. 发明申请
    • METHOD AND APPARATUS FOR USING STATE SPACE DIFFERENTIAL GEOMETRY TO PERFORM NONLINEAR BLIND SOURCE SEPARATION
    • 使用状态空间差分几何进行非线性盲源分离的方法和设备
    • WO2008076680A9
    • 2008-09-18
    • PCT/US2007086907
    • 2007-12-10
    • LEVIN DAVID N
    • LEVIN DAVID N
    • G06F15/00
    • G06K9/6242
    • Given a time series of possibly multicomponent input data, the method and apparatus includes a device that finds a time series of "source" components, which are possibly nonlinear combinations of the input data components and which can be partitioned into groups that are statistically independent of one another. These groups of source components are statistically independent in the sense that the phase space density function of the source time series is approximately equal to the product of density functions, each of which is a function of the components (and their time derivatives) in one of the groups. In a specific embodiment, an unknown mixture of data from multiple independent source systems (e.g., a transmitter of interest and noise producing system) is processed to extract information about at least one source system (e.g., the transmitter of interest).
    • 给定可能的多分量输入数据的时间序列,该方法和设备包括找到时间序列的“源”分量的设备,其可能是输入数据分量的非线性组合,并且可以被分成统计独立于 另一个。 这些源组成部分在统计上是独立的,即源时间序列的相空间密度函数近似等于密度函数的乘积,其中每一个密度函数都是其中一个部分(及其时间导数)的函数 团体。 在具体实施例中,处理来自多个独立源系统(例如,感兴趣的发射机和噪声产生系统)的数据的未知混合,以提取关于至少一个源系统(例如感兴趣的发射机)的信息。
    • 9. 发明申请
    • METHOD AND APPARATUS FOR USING STATE SPACE DIFFERENTIAL GEOMETRY TO PERFORM NONLINEAR BLIND SOURCE SEPARATION
    • 使用状态空间差分几何来执行非线性盲点分离的方法和装置
    • WO2008076680A2
    • 2008-06-26
    • PCT/US2007086907
    • 2007-12-10
    • LEVIN DAVID N
    • LEVIN DAVID N
    • G06F17/14
    • G06K9/6242
    • Given a time series of possibly multicomponent input data, the method and apparatus includes a device that finds a time series of "source" components, which are possibly nonlinear combinations of the input data components and which can be partitioned into groups that are statistically independent of one another. These groups of source components are statistically independent in the sense that the phase space density function of the source time series is approximately equal to the product of density functions, each of which is a function of the components (and their time derivatives) in one of the groups. In a specific embodiment, an unknown mixture of data from multiple independent source systems (e.g., a transmitter of interest and noise producing system) is processed to extract information about at least one source system (e.g., the transmitter of interest).
    • 给定可能的多组分输入数据的时间序列,该方法和装置包括找到“源”分量的时间序列的装置,其可以是输入数据分量的非线性组合,并且可以被划分为在统计学上独立于 另一个。 在源时间序列的相位空间密度函数近似等于密度函数的乘积的意义上,这些源组成部分在统计上是独立的,每个密度函数是组分(及其时间导数)之一的函数, 团体。 在具体实施例中,处理来自多个独立源系统(例如,感兴趣的发射机和噪声产生系统)的未知数据混合,以提取关于至少一个源系统(例如,感兴趣的发射机)的信息。