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parzen.根据样本进行概率密度函数估计
- parzen窗法，功能是根据样本进行概率密度函数估计。实现了对正态分布概率密度函数和均匀分布双峰概密函数进行估计,Parzen window method, function is based on a sample of the estimated probability density function. The realization of the normal distribution probability density function and uniform distributi
Parzen-window-method
- 此为模式识别中Parzen窗法估计概率密度函数。 全部程序流程如下： 1、读取FAMALE.TXT文件把身高或体重给数组，并求x1的样本数N1和窗宽、体宽； 2、读取MALE.TXT文件把身高或体重给数组，并求x2的样本数N2和窗宽、体宽； 3、读取Test2.txt文件把对应的身高或体重给数组A并求A的样本数M； 4、利用Parzen窗法估计概率密度函数判别男女性别； 5、对本判别的错误率进行统计。 -This is the pattern recognition
parzen.rar
- 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
parzen.rar
- 用parzen窗方法，估计概率密度，采用高期核函数。。。。,With parzen window means of estimating the probability density function using high nucleus. . . .
parzen
- 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
Parzen
- 利用parzen窗进行概率密度函数估计，并给出仿真，程序简单易懂。-Using parzen Window probability density function estimation and the simulation, the program is simple to understand.
moshishibie
- 关于模式识别的几个matlab程序，包括fisher；parzen窗；感知函数等等。-Matlab on the number of pattern recognition procedures, including the fisher parzen window perceptual function and so on.
parzen
- 二维数据集Parzen方窗非参数估计PDF(概率密度函数)，三维结果显示，有图，有完整说明文档和程序运行说明，matlab编程环境，此为模式识别小作业 parzen-Dimensional data set Parzen Window non-parametric estimation side PDF (probability density function), three-dimensional results show that map, with complete documentat
parzen
- 这是parzen窗估计的典型例子，大家可以直接学习，是个不可多得的好材料。-This is a typical example of the estimated parzen window, we can learn, is a rare good material.
parzen
- Parzen窗拟合标准正态分布（Matlab实现）-Parzen window fitting the standard normal distribution (Matlab implementation)
Parzen_Window
- 模式识别中Parzen窗函数的实现，模拟对二维高斯分布的非参估计。窗函数有三种：高斯窗、指数窗、方窗-Pattern Recognition Parzen window function of the realization, simulation of two-dimensional Gaussian distribution is estimated non-participation. There are three window function: Gaussian window, th
Parzen
- 调节窗口大小，来捕获数据，而得到函数特征-Adjust window size to capture the data, and function characteristics have been
gaussianparzenwindowdensityestimation
- parzen window density estimation with Gaussian as a smoothing factor
parzen
- 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
classifier
- 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
parzen
- 这是模式识别的一个大作业，其中包括了parzen窗的原理，算法和源程序，还有对结果的分析。-This is a great job of pattern recognition, including parzen window theory, algorithms and source code, as well as the results of the analysis.
parzenwin2
- PARZEN WINDOWN(N) returns the N-point Parzen window in a column vector-PARZEN WINDOWN(N) returns the N-point Parzen window in a column vector
Parzen-window-
- Parzen 窗估计密度函数对图形图像进行处理-Parzen window estimated density function of the graphics processing
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
三步搜索法
- 本实验的目的是学习Parzen窗估计和k最近邻估计方法。在之前的模式识别研究中，我们假设概率密度函数的参数形式已知，即判别函数J(.)的参数是已知的。本节使用非参数化的方法来处理任意形式的概率分布而不必事先考虑概率密度的参数形式。在模式识别中有躲在令人感兴趣的非参数化方法，Parzen窗估计和k最近邻估计就是两种经典的估计法。(The purpose of this experiment is to study the Parzen window estimation and the k nea