Description: lingjian.m-----蒙特卡罗方法
lingjian.m使用零件初始值，用蒙特卡罗方法算出总费用。其中使用了自己编制的正态分布随机数发生器产生正态分布随机数。lingjian.m是对蒙特卡罗方法的一次练习。
accyouhua为标定值的函数，而lingjian不是一个函数，在其中已给出了一组标定值的值。
退火确定标定值/unitanneal()----模拟退火
连续型多个变量组合优化问题
这是对模拟退火方法的一次练习，结果证明模拟退火确实是一个行之有效的方法。
当参数选择较好时（一般也伴随着运行时间的加长），模拟退火的结果较好，然而用MATLAB的FMIMCON()一般可达到更高的精度。-lingjian.m----- Monte Carlo method
lingjian.m part the initial value, using the Monte Carlo method to calculate the total cost. The use of the preparation of their own normal distribution random number generator to produce a normal distribution of random numbers. lingjian.m yes to the first practice of the Monte Carlo method.
accyouhua calibration function, and lingjian is not a function, which has given the value of a set of calibration values .
Annealing to determine the calibration value/unitanneal ()---- Simulated Annealing
Combinatorial optimization problem of continuous multiple variables
This is a practice of simulated annealing method, the results show that simulated annealing is an effective method.
Parameter selection is better (usually accompanied by longer running time) the results of simulated annealing, however the MATLAB FMIMCON () generally achieve higher accuracy.
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Author:王彦钧 |
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Description: 使用C++编程语言，开发了“单壁碳纳米管手性矢量识别系统”软件。软件处理结果显示:采用最大类间方差法二值化单壁碳纳米管STM图像，能够保留较多单壁碳纳米管的六边形拓扑结构信息；采用本文设计的射线探测加权法能够快速、准确的识别出六边形碳环的中心。-The processing result with the software indicated more topology structure information could be reserved, when maximal variance between-class method and minimum bias-normal distribution index method were employed to binarize the STM images of SWCNTs. We designed detect weighing method, which was adopted to recognize the centers of hexagon rings rapidly. Platform: |
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Author:wangmaofa |
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Description: C语言编写的统计学中几种特殊函数值计算的程序代码，包括伽马函数值、正态分布函数值、t分布函数值、贝塔函数值、误差函数值等等。-Code value of several special functions written in C, statistically, including the gamma function value, the value of the normal distribution function, t value of the distribution function, the value of the beta function, the error function value. Platform: |
Size: 17408 |
Author:胡小军 |
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Description: 用C++编写的四种分布类型的点集生成程序，包括Gauss-Kuzmin 分布，正态分布，均匀分布-In C++ to write four distribution types of the point set generator, including the Gauss-Kuzmin distribution, normal distribution, uniform distribution Platform: |
Size: 3203072 |
Author:wendy |
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Description: matlab中，用于求正态分布的累积分布函数的逆函数-matlab for seeking a normal distribution of the inverse function of the cumulative distribution function Platform: |
Size: 4096 |
Author:doujiang |
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Description: 以中等纯度的精馏塔为研究对象，考虑到不等分子溢流的影响和非理想的汽液平衡，可以得到塔顶产品轻组分含量Y与回流量L之间的传递函数为：
其中由于现场环境干扰，输出带有测量噪声是（0，1）的正态分布序列，它的方差为ɑ=0.5。由于输出中带有很大的噪声信号，故将数字滤波技术中常见的低通滤波器由于偏差控制，滤掉其中的噪声信号，然后在对其进行PID计算，得到实际的控制量。在该方法在噪声较强的环境下，可以得到较好的控制效果。
控制要求：
1、 采用带低通滤波器的增量式PID将塔顶轻组分含量控制在0.99
2、 用ISTE法整定PID参数
3、 在控制过程中，到150周期加入幅度为-20 的阶跃干扰，在第300周期干扰消失。分析PID参数的抗干扰性。-Medium-purity distillation column, taking into account ranging from molecular overflow and non-ideal vapor-liquid equilibrium, the transfer function between the light component content of the top product Y and the back flow L can be obtained as:
Because the field of environmental interference, output with the measurement noise is a normal distribution (0,1) sequence, its variance ɑ = 0.5. As with a lot of noise in the output signal, it will be common in low-pass filter in the digital filtering techniques due to the bias control, filter out the noise signal, then its PID, the actual amount of control. In the strong noise environment, you can get better control effect.
Control requirements:
1, using the incremental PID with a low-pass filter to the top of the tower content of light components in the 0.99
2, the method of ISTE tuning PID parameters
3, in the control process, to 150 cycles join the range of-20 step disturbance, disappearance of interference in the first 300 c Platform: |
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Author:孙孙 |
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Description: 伪随机数的产生算法，利用线性同余法产生在（min，max）上精度为4位小数的平均分布的随机数，实现在min 到max 范围内产生服从正态分布的随机数-Pseudo-random number generation algorithm, using the linear congruential method to generate the (min, max) on the accuracy of four decimal evenly distributed random numbers, to achieve a normal distribution of random numbers in the range min to max Platform: |
Size: 2013184 |
Author:judeliu |
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Description: Matlab下利用同余算法产生一组伪随机数，并利用中心极限定理构造正态分布序列，验证其正态性并编写自相关函数计算其自相关-using the congruence algorithm to generate a set of pseudo-random number , and use the central limit theorem to construct a normal distribution sequence, and then verify the normality and use autocorrelation function to calculate the autocorrelation
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Author:wanghusangyi |
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Description: c#实现的概率计算类，提供了正态分布的分布函数、正态分布的反函数、chi2分布的分布函数、chi2分布的反函数、B分布函数、F分布函数、F分布的反函数、t分布的分布函数、t分布的反函数的计算-c# implementation of the probability class, the distribution function of normal distribution, normal distribution function of the anti-chi2 distribution of the distribution function, anti-chi2 distribution function, B distribution function F distribution function, inverse function of the F distribution, t the distribution function of the distribution, the calculation of the inverse function of t distribution Platform: |
Size: 2048 |
Author:于立凯 |
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Description: 在C#中，产生一般随机数用Random即可，但是，若要产生服从特定分布的随机数，就需要一定的算法来支持了，产生服从正态分布、泊松分布、指数分布以及负指数分布随机数的方法-A general random number in C#, you can use Random, but to have to obey a particular distribution of random numbers, you need a certain algorithm to support, resulting in a normal distribution, Poisson distribution, exponential distribution and negative exponential distribution the method of random number Platform: |
Size: 26624 |
Author:于立凯 |
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Description: 《数字信号处理C语言程序集》
内涵各种c语言源码！
第一章 数字信号的产生
均匀分布随机数；正态分布随机数；指数分布随机数....
第二章 快速傅里叶变换
第三章 快速离散正交变换
第四章 快速卷积与相关
第五章 数字滤波器的时域和频域响应
-" Digital Signal Processing C language program set the connotation of a variety of c language source code! The first chapter of the digital signal to produce uniformly distributed random number normal distribution of random numbers exponential distribution random number .... Fast Fourier Transform of the third chapter of fast discrete orthogonal transform the fourth chapter of the fast convolution with the relevant fifth chapter of the digital filter time domain and frequency domain responses .... Platform: |
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Author:笑傲江湖 |
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Description: 用matlab进行概率密度函数的非参数估计，主要有parzen窗法和kn近邻法。分别对平均分布和正态分布进行了仿真。-Non-parametric estimation of the probability density function using matlab, main the parzen window method and kn nearest neighbor method. The average distribution and normal distribution were simulated. Platform: |
Size: 70656 |
Author:jane |
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Description: MATLAB模型：HMIPv6&MIPv6在正态分布HOP数情况下的延迟-MATLAB model: HMIPv6 & MIPv6 delay in the case of normal distribution HOP number Platform: |
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Author:eric |
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Description: machine learning-Density Estimation objects.
parzen - Parzen s windows kernel density estimator
indep - Density estimator which assumes feature independence
bayes - Classifer based on density estimation for each class
gauss - Normal distribution density estimator-machine learning-Density Estimation objects.
parzen - Parzen s windows kernel density estimator
indep - Density estimator which assumes feature independence
bayes - Classifer based on density estimation for each class
gauss - Normal distribution density estimator Platform: |
Size: 14336 |
Author:hossein |
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Description: 用于判断数据属于什么分布，有正态分布、泊松分布等-For the judgment under what distribution, normal distribution, Poisson distribution Platform: |
Size: 1024 |
Author:刘石劬 |
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Description: these are some matlab programs having pdf of normal distribution boinomial distribution poisson distribution. these are taken from well known book anthones paopulus on probability theory Platform: |
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Author:suchit shri |
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Description: The Generalized ESD procedure ( gesd ), tests for up to a prespecified
number r of outliers and it is specially recommended when testing for
outliers among data coming from a normal distribution.-The Generalized ESD procedure ( gesd ), tests for up to a prespecified
number r of outliers and it is specially recommended when testing for
outliers among data coming from a normal distribution. Platform: |
Size: 2048 |
Author:Ali |
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Search - normal distribution