This function makes an iteration of PCA-Gaussianization process
此功能可以使PCA-高斯化过程的迭代
译者:生物统计家园网 机器人LoveR
描述----------Description----------
This function makes an iteration of PCA-Gaussianization process
此功能可以使PCA-高斯化过程的迭代
用法----------Usage----------
GPCA_iteration(x_prev, extremes = TRUE)
参数----------Arguments----------
参数:x_prev
previous set of random variable x
上一组的随机变量x
参数:extremes
see normalizeGaussian_severalstations
看到normalizeGaussian_severalstations
值----------Value----------
A GPCA_iteration S3 object which contains the following objects:
AGPCA_iterationS3对象,它包含以下对象:
x_prev Previous set of random variable, x_prev input variable
x_prev上一组随机变量,x_prev输入变量
x_gauss_prev Marginal Gaussianization of x_prev obtained through normalizeGaussian_severalstations
x_gauss_prev边际高斯化的x_prev获得通过normalizeGaussian_severalstations“
B_prev rotation matrix (i. e. eigenvector matrix of the covariance matrix of x_gauss_prev
B_prev旋转矩阵(即矩阵的特征向量的协方差矩阵x_gauss_prev
x_next results obtained by multiplying B_prev by x_gauss_prev (see equation 1 of the reference)
x_next所得结果乘以B_prevx_gauss_prev(见式(1)的基准)
注意----------Note----------
This function is based on equation (1) of "PCA Gaussianization for One-Class Remote Sensing Image" by V. Laparra et al., www.uv.es/lapeva/papers/SPIE09_one_class.pdf and http://dx.doi.org/doi/10.1117/12.834011
根据式(1)的“PCA高斯化一类的遥感图像”五Laparra等,www.uv.es/lapeva/papers/SPIE09_one_class.pdf和http://dx此功能。 doi.org/doi/10.1117/12.834011