搜索资源列表
gkdj
- 以为高斯和密度估计，使用高斯核的非参数密度估计方法，对样本进行概率密度估计，程序中给出了窗宽的估算公式。-That the Gaussian and density estimation, using Gaussian kernel non-parametric density estimation method, the sample probability density estimates, the program gives the formula for bandwidth estim
dectect
- 基于高斯核密度模型的运动目标检测，适合图像处理专业人员参考-Based on the Gaussian kernel density model of moving target detection for image processing professionals reference
mainKDEprogramLINEAR
- 核密度估计，用于识别和核密度计算，采用高斯插样。-kernel density evalue.it is used for statistical pattern recognition.
KDE
- 对6个样本点，进行直方图估计核高斯核密度估计-for 6 sample points, histogram estimation and Gauss kernel density estimation
Motian_tracing
- 基于高斯核密度函数的运动目标检测程序。参考文章是background and foreground Modeling Using kernel density Estimation for visual surveilence-This programe used in moving object detection, the programe refer to article background and foreground Modeling Using kernel density Est
Parzen-window
- 这是一个有关parzen窗估计的代码，用来估计概率密度函数。采用了方窗、指数窗、高斯窗函数三种核函数，附有matlab程序。-This is an estimate of the code related to parzen window, used to estimate the probability density function. With a side window, the index window, Gaussian window function three kinds of
MutualInfo
- 通过高斯核密度估计计算多元变量之间的互信息熵-The mutual information entropy between multivariate variables is calculated by Gaussian kernel density estimation
caisetidu1
- 用于计算彩色图像的概率密度梯度，核函数选取为高斯核函数(The probability density gradient of color image)
HMDQW
- 用于计算非参数核密度的高斯核密度概率分布函数的期望值(Expected values of the Gauss kernel density probability distribution function for nonparametric kernel density calculations)
kde
- 给定样本点，采用高斯核密度估计，求出概率密度分布函数。(It is good to use this method to evaluate pdf)
CY20180228
- 利用最大熵法求解正态分布的解析解，以及利用高斯核函数计算概率密度(Obtain PDF by maximum entropy and a gaussian kernel function)
kde2d
- 高斯核密度算法，短时傅里叶变化，计算高斯核函数的权重(Gauss kernel density algorithm, short time Fourier change, calculation of the weight of Gauss kernel function)