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05041062
- 1.产生(0-1)分布随机数的方法:z i =(16807zi-1 +1)mod(pow(2,32)).被主函数调用. 2.产生U(0-1)分布利用公式:x1=sqrt(-2lnU1)cos(2PiU2), x2=sqrt(-2lnU1)sin(2PiU2) 3.产生瑞利分布,用两个独立同分布的正态分布值,用公式 x= sqrt(Y1*Y1+Y2*Y2)产生瑞利随机数. 4泊松分布-1. 20 (0-1) random number distribution methods : i
泊松分布是一种常用的离散型概率分布
- 泊松分布是一种常用的离散型概率分布，数学期望为m的泊松分布的分布函数定义如下： P(m, k) = mk * e-m/k! (k = 0, 1, 2, 3, …) 对于给定的m和k (0<m<2000, 0<= k < 2500)，计算其概率，以科学格式输出，保留小数点后6位有效数字。 ,Poisson distribution is a commonly used discrete probability distributions, mathema
Rand.rar
- 随机数生成类。封装c++的rand函数，用于生成均匀、正态、伽马、贝塔、泊松、指数、几何等分布规律的随机数。 内含生成各分布的算法源码。各分布可通过ts测试。,A random number generator class. it Packages the rand function of C++,and is used to generate uniform, normal, gamma, beta, Poisson, exponential, geometric and other dis
matlab-pdf
- 通过matlab代码画出的各种概率密度函数图形仅供参考-By matlab code to draw the beta probability density function graph for reference only
distribution
- 产生均匀分布、正态分布、瑞利分布、泊松分布这几种分布的随机数，包括实现各部分的子函数和主函数-Produce uniform distribution, normal distribution, Rayleigh distribution, Poisson distribution random number distribution of these types, including the realization of the various parts of the Functions a
zuoye
- 利用有限差分法 (Finite Differential Method, FDM)将场域离散为许多小网格，应用差分原理，将求解连续函数的泊松方程问题转换为求解网格节点上的差分方程组的问题。-The use of finite difference method (Finite Differential Method, FDM) will field for many small discrete grid, the application of differential principle, t
poisson_rayleigh
- 用C语言实现的泊松，瑞利，正态分布函数图形仿真-Using C language Poisson, Rayleigh, normal distribution function graphical simulation
Distributed_Multimedia_Networks
- MATLAB程序，TCP流路由，丢包率计算，包括脚本和simulink模块。-runde2.m (Matlab driver s program for activating 40 TCP flows with an AQM router) vdpol2.m (Matlab function for setting up stochastic differential equations for runde2.m) runde3.m (Matlab driver s program to
matlabwork
- 用matlab循环函数法精确对泊松分布函数求和的程序，黄金分割法与进退法求和，求解二次规划问题函数-Matlab function using cycle accurate summation of the Poisson distribution function of the process
MDL_segmenter
- em algorithm - Find approximate solution to Sf = conv(s,f) = d using EM iteration. EM seeks to minimize the Poisson negative log likelihood function J(f) = sum_i {[Sf]_i - (d_i + sigma^2)*log([Sf]_i + sigma^2)}. -em algorithm - Find approxim
Generate-random-variates
- 文件夹中含有三个c文件，各自产生10万个分别服从正态分布，瑞利分布以及泊松分布的随机数，并利用这些随机数在VC中绘制出这些分布的概率密度函数曲线。注意：运行这些程序之前，需先安装文件夹中的setup文件，以便于在VC中制图。-C folder contains three files, each produce 100,000 were subject to normal distribution, Rayleigh distribution and the Poisson distributi
MATLAB
- 这个函数，很重要，不是用不行，这是一个泊松分布，是一个一维的，长度是1000的分布，还可以自己添加plot绘图函数，查看泊松分布。-This function is very important, do not use this function, very important, not with no, this is a poisson distribution is a one-dimensional, length is 1000 distribution, still can add
Poisson--curve-prediction
- 泊松曲线模型被广泛应用在预测中，该代码实现了泊松曲线的预测功能。-Poisson curve model is widely used in prediction, this code will help achieve the Poisson curve prediction function.
cpp_program
- 通信系统中对不同分布函数的c语言实现，主要是高斯分布、瑞利分布、泊松分布等-Communication system on the distribution function of c language, mainly the Gaussian distribution, Rayleigh distribution, the Poisson distribution
Poisson
- 利用MATLAB写出 Poisson 概率给定到达率求出 Poisson 分布的机率质量函数-Use MATLAB to write the Poisson probability of a given arrival rate to calculate the Poisson distribution of the probability mass function
Judgment-function-distribution-code
- 判断一组数据的概率分布函数，包括正态分布、泊松分布、伽马分布等。-The probability distribution function to determine a set of data, including a normal distribution, the Poisson distribution, gamma distribution.
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
poisson
- poisson过程的分布及其自相关函数，方差函数，平均值-poisson process distribution and autocorrelation function, variance function, average
Poisson-Image-Editing-master
- 泊松编辑的matlab代码，主要实现图像融合功能。-Poisson editor of matlab code, and main function of image fusion.
New folder
- poisson方程的求解及残差比较，最后作网格图，解的图和残差的图(the solution of poisson function and error)