分析了非线性变换对图像产生的影响,提出一种复合变换补偿的方法。
This paper analyzed the effect of general nonlinear transformation to images, and proposed a composite transformation method.
基本思想是通过非线性变换,使样本变换之后的特征空间中变得线性可分。
Basic idea is to adoption of non-linear transform, so that after changing the characteristics of the sample space become linearly separable.
比较了基于广义高斯分布近似和非线性变换(NLMIR)的两种最小互信息盲接收算法。
Minimum mutual information blind receiver that based on approximated generalized Gaussian distribution (GGMIR) and that use nonlinear transformation (NLMIR) are compared.
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