本文基于可辨识矩阵提出一种连续属性离散化的方法，并利用平均互信息量对离散化结果进行修正。
The paper puts forward a method of discretization of continuous properties based on discernibility matrix and revises the discrete result by average mutual information.
基于互信息的图像配准方法具有自动化程度高、配准精度高等优点，已被广泛应用于医学图像的配准。
Image registration based on mutual information is of high automatization and high accuracy in registration. Hence, it has been widely exploited in medical image registration.
采用输出信号的广义高斯分布近似，基于互信息最小化目标函数自适应调整均衡器的系数。
Based on method of minimizing of mutual information and approximated generalized Gaussian distribution of equalized output signal, the equalizer changes its coefficients adaptively.
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