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EM algorithm using matlab
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模式识别的内容,包括模式识别的基本概念、模式识别方法及应用。具体的内容包括:正则化网络、Bayes决策理论、分类器组合、统计学习理论、概率密度估计、非监督学习方法-Pattern recognition, including the basic concepts of pattern recognition, pattern recognition methods and applications.Specific content, including: Regularization Netwo
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Why Naive Bayes?
Naive Bayes is one of the simplest density estimation methods from which
we can form one of the standard classiˉcation methods in machine learning.
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核密度估计,目标检测,图像处理,希望有用-Kernel Density Estimation
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自适应核密度估计运动检测方法 提出一种自适应的核密度(kernel density estimation, KDE)估计运动检测算法. 算法首先提出一种自适应前景、背景阈值的双阈值选择方法, 用于像素素分类. 该方法用双阈值能克服用单阈值分类存在的不足, 阈值的选择能自适应进行, 且能适应不同的场景. 在此基础上, 本文提出了基于概率的背景更新模型, 按照像素的概率来更新背景, 并利用帧间差分背景模
-Adaptive kernel density estimation motion det
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机器学习matlab源代码,包括多分类SVM,模式识别,特征选择,回归等算法。-The spider is intended to be a complete object orientated environment for machine learning in Matlab. Aside from easy use of base learning algorithms, algorithms can be plugged together and can be compared with
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基于核密度估计的背景减法算法,拥有命令行界面的C++源代码。-kernel density estimation based background subtraction algorithm [1] with a command line interface. this algorithm is a somewhat improved version of [2].
the kmovingobjdetector class within the project is originally w
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几种功率谱密度估计的方法,有古典功率谱估计和现代功率谱估计-Several power spectral density estimation method, a classical power spectrum estimation and modern power spectrum estimation
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Locally Adaptive Kernel Density Estimation
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Locally Adaptive Kernel Density Estimation
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核密度估计,可以刻画变量的时间演进动态性,可以反映变量在时间上的变动的整体性- Kernel Density Estimation
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本文提出了一种基于小波变换与灰度共生矩阵的人群密度特征提取方法,进而利用支撑向量机实现人群密度级别的估
计。实验结果表明本文提出的方法是可行的。-In this paper, based on population density characteristics of the wavelet transform and GLCM extraction method, and then using the support vector machine to estimate the crowd
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基于非参数概率密度估计的盲源分离算法(NpICA),使用matlab编程,有可视界面。-Non-parametric probability density estimation-based blind source separation algorithm (NpICA), using the Matlab programming, visual interface.
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信号处理中的振幅谱和相位谱以及谱密度估计等-1) Calculation of:
- One-sided amplitude spectrum
- One-sided phase spectrum
- Vector of frequencies.
2) The function can plot:
- One-sided amplitude spectrum
- One-sided phase spectrum.
Two examples are g
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K近邻估计方法,采用可变大小的小舱的密度估计方法。-K-nearest neighbor estimation method, the size of a small cabin with variable density estimation method.
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对输入视频进行处理,使用高斯背景建模的方法,得到视频前景,对于人群密度估计具有很大作用。-Processing of the input video, using a Gaussian background modeling method, to get videos prospects for population density estimation has a significant role.
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K最邻近密度估计分类,K最邻近密度估计技术是一种分类方法,不是聚类方法。-K nearest neighbor classification density estimation, K nearest neighbor density estimation technique is a classification method, not the clustering method.
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核密度估计的parzen窗法,简单易用,适合于初学非参数估计的用户。-Kernel Density Estimation parzen window method, easy to use, suitable for novice non-parametric estimation of the user.
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核密度估计 C程序 自己编写 适合初学者-Kernel Density Estimation write your own C program
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功率谱密度的估计算法,simulink实现,现代信号处理第三章仿真实现。-Power spectral density estimation algorithm, simulink realization of modern signal processing Chapter Simulation.
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