首页> 外国专利> Real-time multi-channel EEG signal processor based on on-line recursive independent component analysis

Real-time multi-channel EEG signal processor based on on-line recursive independent component analysis

机译:基于在线递归独立分量分析的实时多通道脑电信号处理器

摘要

A real-time multi-channel EEG signal processor based on an on-line recursive independent component analysis is provided. A whitening unit generates covariance matrix by computing covariance according to a received sampling signal. A covariance matrix generates a whitening matrix by a computation of an inverse square root matrix calculation unit. An ORICA calculation unit computes the sampling signal and the whitening matrix to obtain a post-whitening sampling signal. The post-whitening sampling signal and an unmixing matrix implement an independent component analysis computation to obtain an independent component data. An ORICA training unit implements training of the unmixing matrix according to the independent component data to generate a new unmixing matrix. The ORICA calculation unit may use the new unmixing matrix to implement an independent component analysis computation. Hardware complexity and power consumption can be reduced by sharing registers and arithmetic calculation units.
机译:提供了一种基于在线递归独立分量分析的实时多通道脑电信号处理器。白化单元通过根据接收到的采样信号计算协方差来生成协方差矩阵。协方差矩阵通过平方反方根矩阵计算单元的计算来生成白化矩阵。 ORICA计算单元计算采样信号和白化矩阵以获得白化后采样信号。白化后采样信号和解混矩阵实现独立分量分析计算以获得独立分量数据。 ORICA训练单元根据独立分量数据对分解矩阵进行训练,以生成新的分解矩阵。 ORICA计算单元可以使用新的分解矩阵来实现独立的成分分析计算。共享寄存器和算术计算单元可以降低硬件复杂性和功耗。

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