guihuawenti

Matlab教程PPT，Matlab概述与应用程序基础(Matlab PPT)

matlab模糊逻辑工具箱函数，模糊控制时非常有用的资料(matlab fuzzy logic toolbox function, fuzzy control of very useful information )

短时综合的滤波器组相加法的matlab程序的实现，使用的是先调制后滤波的方法(Synthesis filter bank to achieve short-sum method matlab program, using a filter after the first modulation method)

by matlab draw the julia set and mandelbrot set.

完成3gpp标准中LTE系统16QAM调制方式的编码，该附件为子函数，输入bit流即可(Completion of 16QAM modulation coding 3gpp standard LTE system, the attachment of Functions, input bit stream can be)

application C# pour calcul de multiplication

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 )

利用R的toepliz性质，是实数，则r也应该是实数，是实信号r(-m)=r(m)(Toepliz the nature of the use of R is real number, then r should be real, real signal r (-m) = r (m))

单个圆椭球干扰计算(根据切片法理论计算)(Single round ellipsoid interference calculations)

ABC算法的源码找来逐行做了中文注释，并以优化SVM参数为例，进行学习。(ABC algorithm source code got to do a progressive Chinese comments, and to optimize the SVM parameters, for example, to learn.)