floyd-shortest-path-algorithm

数值分析的牛顿迭代算法数值分析的牛顿迭代算法(matlab )

this file simulates encoding turbo by using matlab

matlab信号处理常用函数参考书，分类清晰明了，对信号处理函数做了很好的分类，便于查询。(commonly used signal processing matlab function reference, classification clarity of the signal processing functions done a very good classification, easy to query.)

matlab源程序,用Sobel算子和拉普拉斯对图像锐化(Matlab source code, image sharpening of Sobel operator and Laplasse )

C++ balagurswamy E-Book for new beginners in c++.

程序1实现了一维Airybeam的三维图形，从x-y面可以看出Airybeam的传输轨迹，三维图形的z轴是光强； 程序2实现了1维Airybeam的轨迹控制，通过改变wm和wg的值可使光强的最大值在任意位置。(A three-dimensional graphics program to achieve a one-dimensional Airybeam the xy plane can be seen Airybeam transfer trajectory, and three-dimensional graphics z-axis is the light intensity 2 implements the program track 1-dimensional Airybeam control, by changing the value of wg wm and the light intensity at an arbitrary position allows the maximum.)

说明：  此为C++环境下的LDPC编译码的完整的源代码。常用于通信系统的编译码仿真过程。有助于各种项目的完成。(This is the C++ environment LDPC coding and decoding of the complete source code. Commonly used in the encoding and decoding communication system simulation. Contribute to the completion of various projects.)

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 )

一個簡單的小程式用於建構Markowitz投資組合。(This program is used for modeling Markowitz portfolio.)

一种可以对数据的鲁棒性进行消除的工具箱 可以对数据进行加权(A way to the robustness of the data to eliminate the data can be weighted toolbox)