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模式识别 作业 实现自动产生样本,并用最近距离法,贝叶斯分类,Parzen窗概率密度估计-Pattern recognition operations automatically generate the sample, and with the recent distance method, Bayesian classifier, Parzen window probability density estimation
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The Parzen-window Density Estimation
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Parzen窗估计法是一种非参数函数估计方法,它能够较好地描述多维数据的分布状态。其基本思想就是利用一定范围内各点密度的平均值对总体密度函数进行估计。-Parzen window estimation method is a nonparametric function estimation method, which can describe the distribution of multi-dimensional data. The basic idea is to use the ave
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核密度估计,matlabkernel density estimation是在概率论中用来估计未知的密度函数,属于非参数检验方法之一,由Rosenblatt (1955)和Emanuel Parzen(1962)提出,又名Parzen窗(Parzen window)。Ruppert和Cline基于数据集密度函数聚类算法提出修订的核密度估计方法。-kernel density estimation
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Multispectral remotely sensing imagery with high
spatial resolution, such as QuickBird, IKONOS satellite
imagery or Aerial imagery, especially in urban scenes, often
perform spectral variations and rich details within a category,
resulting in
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