extr

单自由度系统对初始条件和简谐激励相应 由单自由度的运动方程和初始条件得到二阶非齐次常微分方程，它的解有对应的齐次方程的通解和非齐次方程的特接构成。(Single degree of freedom system to initial conditions and the corresponding harmonic excitation Special general solution of the equations of motion and initial conditions by a single degree of freedom to get the second order non-homogeneous ordinary differential equations, its solution has a corresponding homogeneous equation and non-homogeneous equation then constituted.)

这是模式识别中最小风险Bayes分类器的设计方案。在参考例程的情况下，自行完善了在一定先验概率的条件下，男、女错误率和总错误率的统计，放入各个数组当中。 全部程序由主函数、最大似然估计求取概率密度子函数、最小错误率贝叶斯分类器决策子函数三块组成。 调用最大似然估计求取概率密度子函数时，第一步获取样本数据，存储为矩阵；第二步对矩阵的每一行求和，并除以样本总数N，得到平均值向量；第三步是应用公式（3-43）采用矩阵运算和循环控制语句，求得协方差矩阵；第四步通过协方差矩阵求得方差和相关系数，从而得到概率密度函数。 调用最小风险贝叶斯分类器决策子函数时，根据先验概率，再根据自行给出的5*5的决策表，通过比较概率大小判断一个体重身高二维向量代表的人是男是女，放入决策数组中。 主函数第一步打开“MAIL.TXT”和“FEMALE.TXT”文件，并调用最大似然估计求取概率密度子函数，对分类器进行训练。第二步打开“test2.txt”，调用最小风险贝叶斯分类器决策子函数，然后再将数组中逐一与已知性别的数据比较，就可以得到在一定先验概率条件下，决策表中不同决策的错误率的统计。 (This is a pattern recognition classifier minimum risk Bayes design .In reference to the case of routine , self- improvement in a certain a priori probability conditions, male , female and total error rate error rate statistics , into which each array . All programs from the main function , maximum likelihood estimation subroutine strike probability density , the minimum error rate Bayesian classifier composed of decision-making three subfunctions . Strike called maximum likelihood estimate probability density subroutine , the first step to obtain the sample data , stored as a matrix the second step of the matrix, each row sum , and divided by the total number of samples N, be the average vector The third step is the application of the formula ( 3-43 ) using matrix and loop control statements , obtain the covariance matrix fourth step through the variance-covariance matrix and correlation coefficient obtained , resulting in the probability density function . Bayesian classifier )

poisson 求解 Benchmarks several different ways of generating Compound Poisson random variables by Monte Carlo simulation.(compound poisson Benchmarks several different ways of generating Compound Poisson random variables by Monte Carlo simulation.)

这是基于MATLAB的仿真自适应的算法程序。他简单的描述了自适应的过程(it is a program about zi shi ying. it based on matlab)

用于生成FPGA中RAM所需要的初始化文件dds.mif,此文件生成的是余弦波形。(This document of .m can generate document of .mif to provide data for RAM of FPGA.)

ti so PAPR trong LTE-Advance

1. 608组样本，第一列数字是标号，第二列数字是出现损坏的时间，第三列表示数据有效性，为0有效 2. 损坏时间是对数正态分布的，需要拟合 3. 求均值80%置信区间 4. 成本为m，价格为s，保证盈利20%，选取保修期 5. 比较保修期和拟合数据的均值 6. 若保修期就是拟合损坏时间的均值，求出利润率 loadd.m：加载样本数据，并选取有效数据 period.m：加载成本、价格数据，计算利润和保修期的关系(1.608 groups of samples, the first number is the label, the second column number is the time to appear damage, the third list shows the validity of the data, which is 0 effective. 2. damage times are logarithmic normal distribution and need to be fitted 3. mean in 80% confidence interval 4. the cost is m, the price is s, the profit is 20%, the warranty period is selected. 5. compare the mean value of the warranty period and the fitting data 6. if the warranty period is to fit the mean damage time, the profit rate is calculated. Loadd.m: load the sample data and select the valid data Period.m: loading cost, price data, and calculating the relationship between profit and warranty period)

For multiple boards in a test suite, this function displays the wind, starting and end points and maximum wind. For each solver for each board, the boat path and thrust adjustments are displayed. In the legend, the solver name, score, and thrust usage for each path is displayed

B-Spline Surface (with redundant points) Least-Squares Fitting of both Positions and Normals.

matlab 源代码分析，适用于rf工程师学习天线设计，结合hfss的源代码分析(matlab source code analysis for engineers to learn rf antenna design, combined with source code analysis hfss)