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在图像处理中经常涉及分类，多次有用到非参数估计。本程序用Parzen窗来估计，用随机高斯函数来作计策信号.-in image processing involves classification, the many useful to the non - parametric estimation. The procedure used to estimate Parzen window, using random Gaussian function to signal for the ploy
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这是一个parzen窗口分类算法，希望能给大家的学习有所帮助,This is a Parzen window classification algorithm, we hope that they will be helpful to the learning
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这是一个模式识别中的parzen窗的一个简单仿真分类实例，其中female.txt和male.txt是训练样本，test.txt是测试样本，分类效果非常好，对于模式学习的初学者将会有很大帮助。-This is a pattern recognition in a simple window parzen Category simulation examples, one of female.txt and male.txt training samples, test.txt is the me
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分类器的训练与学习是模式识别的一个重要环节,其目的在于按照某种算法,确定判决规则,使之具有自动分类识别的能力。本文介绍了采用Parzen窗法的随机模式分类器,并matlab实现了一个简易的随机模式分类器。-Classifier training and learning is an important part of pattern recognition, in accordance with the purpose of some kind of algorithm to determine
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两类二维相关正态分布条件下的最小错误率贝叶斯分类器，基于最小风险的贝叶斯分类器，Parzen窗法非参数估计分类器程序，Fisher线性判别法分类器程序。-Under normal conditions two types of two-dimensional correlation of minimum error rate of Bayesian classifier, the minimum risk-based Bayesian classifier, Parzen window meth
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本实验的目的是了解非参数估计--parzen窗估计，对数据进行Parzen窗估计和设计分类器。并分析窗口宽度h对分类的影响。-The purpose of this study is to understand the non-parametric estimation- parzen window estimation, Parzen window estimate of the data and design of classifiers. Window width h and analyz
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用parzen来计算所选的数据的概率密度函数，所选的窗函数是方窗，最后基于最小错误率的贝叶斯进行分类-With parzen selected data to calculate the probability density function, the selected window function is the side window, and finally the smallest error rate based on Bayesian classification
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模式识别的分类函数，包括PCA，风险贝叶斯，最小误差贝叶斯，parzen窗函数等等。-Pattern recognition classification functions, including PCA, risk Bayesian minimum error the Bayesian, parzen window function, and so on.
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基于parzen窗口的贝叶斯分类，先对数据进行训练，再对测试数据进行识别。-Bayesian classification based on parzen window of data, training, and identification of the test data.
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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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模式识别的一些基本的算法，有最大最小距离分类法，简单的感知器算法，LMSE算法，以及Parzen窗函数。-Pattern recognition of some basic algorithms, have the largest minimum distance classification, simple perceptron algorithm, LMSE algorithm, as well as the Parzen window function.
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模式识别在MATLAB程序下的有关算法程序，包括Fisher分类，ML分类，parzen窗分类，直方图画法，roc曲线，roc分类等(Pattern recognition in the MATLAB program related algorithm program, including Fisher classification, ML classification, Parzen window classification, histogram drawing, ROC curve, RO
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