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this folder contain implemetation of three classifier in matlab

蔡氏电路MATLAB仿真程序，分析，绘图，手动设置参数(Chua' s circuit simulation program MATLAB, analysis, mapping, set the parameters manually)

关于MATLAB的GUI界面学习。可以从这个程序中学习GUI界面的编程。(About the MATLAB GUI interface to learn.You can learn from this program GUI interface programming.)

LMS adaptive beamforming MATLAB program

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 )

矩阵积和式双元素Laplace展开，利用Laplace展开递归计算矩阵积和式(the laplace expansion of matrix permanent)

说明：  该算法为基于CMAC与PID并行控制的SIMUlink仿真 用MATlab开发，能够管直接运行(The algorithm based on CMAC and PID control parallel simulation using Matlab Simulink development, be able to pipe directly to run)

KZK parameters.m - User-defined material/transducer parameters

此代码应用于将xml文件转换为mat文件。在图像的目标识别时我们需要获得一些图像的点坐标。但是通过label me。我们只能获得xml文件的形式，这样我们就需要将xml文件转换为mat文件。方便在matlab的语言环境中进行处理(This code is used in the xml file into mat file. When the target image recognition we need at some point in image coordinates. But by label me. We can only get in the form of xml files, so we need to convert the file to mat xml file. Facilitate processing matlab language environment)

基于交通车辆识别的边缘检测，可以得到车辆的边界从而获得车的数量(Edge detection based on the identification of the transport vehicles can be obtained by the quantity of the boundary of the vehicle thereby obtaining Cart)