Description: 对模糊变量进行随机化，并用高斯分布进行概率求解，无密码-pair of fuzzy random variables, and using Gaussian probability distribution solution without passwords Platform: |
Size: 16384 |
Author:宋淑芳 |
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Description: 一个关于高斯模型的概率分布图的生成的小程序，欢迎下载-a Gaussian model of the probability distribution graph generation of small procedures, welcomed Download Platform: |
Size: 1024 |
Author:李菲 |
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Description: matlab环境下，采用指定个数的高斯信号对任意概率分布的信号进行模拟-matlab environment, using the specified number of Gaussian signals for any probability distribution of the signal to simulate Platform: |
Size: 15360 |
Author:fantao |
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Description: 附件中的m代码包括了一系列的拟合函数，这些函数通常的输入是概率分布的样本。还有最大似然估计仿真器、最小平方仿真器、混合高斯分布估计的EM算法、-M in the annex to the code, including a series of fitting function, which function normally is the probability distribution of input samples. There are maximum likelihood estimation simulator, emulator least squares, mixed-Gaussian distribution is estimated that the EM algorithm, Platform: |
Size: 68608 |
Author:liyuedsg |
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Description: 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines-
This section should give the reader a quick overview of the methods implemented in
STPRtool.
• Analysis of linear discriminant function: Perceptron algorithm and multiclass
modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection
of known algorithms solving the Generalized Anderson’s Task.
• Feature extraction: Linear Discriminant Analysis. Principal Component Analysis
(PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis.
• Probability distribution estimation and clustering: Gaussian Mixture
Models. Expectation-Maximization algorithm. Minimax probability estimation.
K-means clustering.
• Support Vector and other Kernel Machines: Sequential Minimal Optimizer
(SMO). Matlab Optimization toolbox based algorithms. Interface to the
SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers.
Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell-
Demyanov-Molozenov algorithm Platform: |
Size: 4271104 |
Author:查日东 |
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Description: 本实验要求根据课本中给出的高斯噪声和椒盐噪声的概率分布的形状和参数编写两个通用程序分别给一个图像中添加高斯噪声和椒盐噪声。高斯噪声是n维分布都服从高斯分布的噪声，椒盐噪声是图像中经常见到的一种噪声是一种随机的黑点或者白点。在实验中通过它们对应的概率密度函数得到噪声分布函数进而与原图像进行叠加产生出对应的噪声图像-Textbooks in this experiment are given under the Gaussian noise and salt and pepper noise in the shape of the probability distribution and parameters of common procedures for the preparation of the two images were added to a Gaussian noise and salt and pepper noise. Gaussian noise is subject to the distribution of n-dimensional Gaussian noise, salt and pepper noise is often the image to see a noise is a random white spots or black spots. In the experiment through their corresponding probability density function of the noise distribution function to be the original image superimposed with the corresponding noise generated image Platform: |
Size: 243712 |
Author:jhm |
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Description: 利用matlab实现高斯分布、指数分布、正太分布等概率分布的方法。-Using matlab to achieve Gaussian distribution, exponential distribution, is too distribution probability distribution method. Platform: |
Size: 2048 |
Author:francis |
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Description: 常见概率分布的随机数生成程序，包括均晕分布、高斯分布、对数正态分布、K分布、t分布、韦布尔分布。-Common probability distribution of the random number generation process, including both halo distribution, Gaussian distribution, lognormal distribution, K distribution, t distribution, Weibull distribution. Platform: |
Size: 2048 |
Author:袁浩 |
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Description: 根据伪随机序列理论，由混合同余法产生均匀分布的随机数，进而根据中心极限定理来产生高斯噪声。
分析所产生的均匀分布和高斯分布随机信号的均值、方差、自相关等数字特征，估计其概率密度函数并进行分析，估计其功率谱密度并进行分析。说明该高斯噪声是否符合白噪声特性。
对该高斯噪声进行FIR低通滤波，估计输出低通型限带白噪声的功率谱、相关时间等，并结合白噪声通过线性系统相关理论来进行分析。
-According to the theory of pseudo-random sequence, a uniformly distributed random numbers by mixed congruential method to generate Gaussian noise, and then according to the central limit theorem. Produce a uniform distribution of the analysis and the mean of the Gaussian distribution random signals, variance, since the digital characteristics of the correlation, the probability density function is estimated and analyzed, it is estimated that its power spectral density, and analyzed. The Gaussian noise is in line with the characteristics of white noise. FIR low pass filter of the Gaussian noise, the estimated output of low-pass type band-limited white noise power spectrum, time, etc., combined with the white noise to be analyzed by linear system theory. Platform: |
Size: 1024 |
Author:Lee |
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Description: 高斯模型就是用高斯概率密度函数（正态分布曲线）精确地量化事物，将一个事物分解为若干的基于高斯概率密度函数（正态分布曲线）形成的模型。(Gaussian model is to use Gaussian probability density function (normal distribution curve) to accurately quantify things, a thing is divided into several based on the Gaussian probability density function (normal distribution curve) to form the model.) Platform: |
Size: 11264 |
Author:Byydyh
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