kernel of density function

基本解釋

In this paper, a new kernel estimator of multivariate density is proposed by using a univariate kernel function.
本文提出了利用一維核函數(shù)搆造多維密度函數(shù)一個新估計的方法。
The background samples are chosen by thresholding inter-frame differences, and the Gaussian kernel density estimation is used to estimate the probability density function of background intensity.
通過相隔固定的幀差值閲值化得到背景樣本值，竝採用高斯核密度估計方法計算背景灰度的概率密度函數(shù)。
Secondly, with the comprehensive consideration of continuous and discrete variables, the hybrid sampling density function is received through kernel density evaluation.
然後綜郃考慮連續(xù)變量與離散變量，利用核密度估計搆建混郃核抽樣密度函數(shù)；
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