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Q1
- 2类分类高斯模型 每个类是由一个单一的多元高斯分布的3-D建模 显示如何估计高斯均值向量和协方差矩阵的最大似然（ML）估计的基础上为每个类。 meanA和meanB代表每个类的均值，varA和varB的的代表每个类的协方差矩阵.-2-class classifier with Gaussian Models Each class is modelled by a single 3-D multivariate Gaussian distribution Show
bayes-classifier-
- 程序展示了bayes classifier对于连续数据的应用，假设数据均服从高斯分布。程序包含了binary classification和multi-classification的例子。-Program shows bayes classifier for continuous data applications, assume that the data are Gaussian. Program includes a binary classification and multi-clas
dsp
- 高斯分布的随机数的生成代码.基于Uniform随机函数的生成-Gauss Distribution Random Number Generation Code, based on uniform random number
Radar-signal-processing
- 雷达信号的基本模型，高斯分布，几何分布，求信号的概率分布，概率密度函数，功率谱函数，自相关函数-The basic model of the radar signal, Gaussian distribution, geometric distribution, the probability distribution for the signal, probability density function, power spectrum, the autocorrelation functio
progream
- Gaussian noise refers to its obey gaussian probability density function (i.e., normal distribution) of the noise. If a noise, its amplitude distribution obeys the gaussian distribution, and its power spectral density is uniformly distributed, has des
ASD
- 所谓高斯噪声是指它的概率密度函数服从高斯分布（即正态分布）的一类噪声。如果一个噪声，它的幅度分布服从高斯分布，而它的功率谱密度又是均匀分布的，则称它为高斯白噪声。高斯白噪声的二阶矩不相关，一阶矩为常数，是指先后信号在时间上的相关性。高斯白噪声包括热噪声和散粒噪声。-Gaussian noise refers to its obey gaussian probability density function (i.e., normal distribution) of the noise. If
qwe
- 所谓高斯噪声是指它的概率密度函数服从高斯分布（即正态分布）的一类噪声。如果一个噪声，它的幅度分布服从高斯分布，而它的功率谱密度又是均匀分布的，则称它为高斯白噪声。高斯白噪声的二阶矩不相关，一阶矩为常数，是指先后信号在时间上的相关性。高斯白噪声包括热噪声和散粒噪声。-Gaussian noise refers to its obey gaussian probability density function (i.e., normal distribution) of the noise. If
wer
- 所谓高斯噪声是指它的概率密度函数服从高斯分布（即正态分布）的一类噪声。如果一个噪声，它的幅度分布服从高斯分布，而它的功率谱密度又是均匀分布的，则称它为高斯白噪声。高斯白噪声的二阶矩不相关，一阶矩为常数，是指先后信号在时间上的相关性。高斯白噪声包括热噪声和散粒噪声。 -Gaussian noise refers to its obey gaussian probability density function (i.e., normal distribution) of the noise.
zaosheng11
- 雷达高斯分布相干视频噪声和高斯分布中频噪声仿真-Coherent Radar Gaussian noise and Gaussian frequency video noise simulation
Gaussian
- 首先产生均匀分布，然后通过变换产生高斯分布的随机数，并画出概率密度函数的直方图-Uniform distribution generated first, and then converting a Gaussian distribution random number, and a histogram of the probability density function draw
Poisson
- 首先产生高斯分布，然后通过变换产生泊松分布的随机数，并画出概率密度函数的直方图-First, a Gaussian distribution, and then transform Poisson distributed random number generation, and draw a histogram of the probability density function
Rayleigh
- 首先产生高斯分布，然后通过变换产生瑞利分布的随机数，并画出概率密度函数的直方图-First, a Gaussian distribution, and then transform Rayleigh distributed random numbers, and draw a histogram of the probability density function
APDL
- 三维移动高斯分布热源表面焊命令流,加快速度快lad连锁店-three asdjj asdqwe asd
05
- 利用蒙特卡罗方法，用洛伦兹分布对高斯分布进行舍选抽样。-Using the Monte Carlo method, using Lorentz distribution on the Gaussian distribution is rounded selection sampling.
MOG
- 拟合高斯分布，对数据点进行拟合给出数据均值和协方差，画图-Fitting of gaussian distribution, logarithmic stronghold fitting given data mean and covariance, the drawing
guass
- 这是一个生成高斯分布的c++（.cc）程序，此程序在linux下g++下编译通过。生成的高斯分布随机数序列的期望为0.0，方差为1.0。若指定期望为E，方差为V，则只需增加：GaussRand() * V + E。http://imatlab.lofter.com/ 欢迎交流学习经验-A gaussian/normal distribution program in linux g++.
nGpFBMP-ver-1.0
- 非高斯分布信号的快速重构算法,该代码为论文“A Fast Non-Gaussian Bayesian Matching Pursuit Method for Sparse Reconstruction”论文的源代码-Fast reconstruction algorithm of non-Gaussian signal The code for the paper "A Fast Non-Gaussian Bayesian Matching Pursuit Method for Sparse
GUASS-RAILY-POSSION
- 高斯分布，瑞利分布，泊松分布,产生符合这三个分布的随机序列-Gaussian distribution, Rayleigh distribution, Poisson distribution, that meets these three distributed random sequence
Desktop
- 本次作业采用了三种不同的算法，分别产生高斯分布、瑞利分布、泊松分布的随机变量，对随机变量本身的熟悉是很重要的-This operation using three different algorithms generate Gaussian, Rayleigh, Poisson random variables, random variables familiar itself is very important
12
- EM 混合高斯分布的相关程序，主要以三个为例-EM mixed Gaussian distribution