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2下载:
利用Gauss核密度估计求窗口宽度,只需导入源数据和修改窗口宽度即可计算最优的窗口宽度,方便,简单,实用-Use Gauss kernel density estimation window width requirements, simply import the source data and modify the window width to calculate the optimal width of the window, convenient, simple, practical
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背景建模是实现运动目标检测与跟踪的关键技术之一。在实时视频监控系统中,对背景建模算法的运行时间及所提取出的背景图像的实时性有很高的要求,针对这一问题,提出了一种基于切比雪夫不等式的自适应阈值背景建模算法。算法利用切比雪夫不等式计算像素点色度变化的概率估计值,提出了一种自适应阈值分类方法,它将像素点快速分类为前景点、背景点及可疑点,再利用核密度估计方法对可疑点进行进一步分类,最后利用背景更新算法提取实时背景图像。实验结果证明,该算法能快速有效地区分特征明显的背景点与前景点,提高了背景图像提取的速
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针对核密度估计背景建模方法运算量大难以实时应用的问题,提出了一种基于背景直方图分布的快速核密度估计背景建模方法。选用三角核函数进行核密度估计,根据三角核带宽函数的截断效应,引入背景分布的直方图完成快速背景建模,在保证目标检测准确性的同时提高运算速度。测试实验结果验证了算法能够满足监控系统的实时性要求。-For kernel density estimation is difficult to satisfy real-time applications because of large amou
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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
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用窗函数实现Iris数据密度估计,使用的函数有正太分布函数,指数函数和均匀分布函数-Window function to achieve Iris data density estimation, there is too function uses the distribution functions, exponential functions and uniform distribution function
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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
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以最优的窗宽进行核密度估计,误差小,比matlab自带程序精确-To the best window width nuclear density estimation, a small error, accurate than matlab own procedures
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核密度估计,绘制频率直方图、核密度估计图、正态分布密度图-Kernel density estimation, drawing frequency histograms, kernel density estimation map, normal density map
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实现k维度的核密度估计,包含了点积核和常规核函数的实现-implement k-dimensional kernel density estimation, supports product kernels ,Gausiankernel 。
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核概率密度估计算法,对于以往的有优化,可以得到概率密度及分布函数。-Nuclear probability density estimation algorithm optimized for the past there, you can get the probability density and distribution functions.
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Matlab implementation of the Kernel Density estimation for 2D array/matrix
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MATLAB code that implements the univari-ate adaptive mixtures density estimation procedure.
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本程序仿真了高斯噪声的几种概率密度估计方法-This procedure simulated several Gaussian noise probability density estimation method
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三维核密度估计法的设计与实现,需要的请自行下载-Design and implementation of a three-dimensional kernel density estimation method, please download their own needs
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基于核密度估计的层次聚类算法 -hierarchcial clustering with kernel density estimation
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The Parzen-window Density Estimation
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KDE 核密度估计算法 运动目标检测算法之一 只进行了第一阶段的运算 具体看原论文-One of the algorithms of moving object detection algorithm was only the first stage of the operation of the specific look of the original paper of kernel density estimation
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均值漂移算法是一种基于颜色特征的无参密度估计算法,被人们广泛的应用于图像滤波、聚类分析和目标跟踪等领域。-Mean shift algorithm is a nonparametric density estimation algorithm based on color feature, which is widely used in the fields of image filtering, clustering analysis and target tracking.
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聚类算法之高斯混合模型,GMM 和 k-means 很像,不过 GMM 是学习出一些概率密度函数来(所以 GMM 除了用在 clustering 上之外,还经常被用于 density estimation )。-Gaussian mixture model of clustering algorithm, GMM and k-means like, but GMM is learning some probability density function (so GMM except on cl
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2015年最新国外算法,基于加权视觉词典的人群密度估计-crowd entimatin by a weighted bag of visual word model
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