exerciciosrobotica

matlab在化学中的应用，有很多例子 是转载的(matlab in chemistry, there are many examples are reproduced)

是基于matlab gui的一些控件的创制，有创建编辑框、文本框，按钮等(Matlab gui is based on a number of controls created, there is created edit box, text boxes, buttons, etc.)

new principle in RADAR and LIDAR with pulse compression and ifft and fft

说明：  分别使用库函数和自编函数实现AR模型谱估计 (Respectively, the use of library functions and the self-function AR model spectrum estimation)

说明：  拟合各种常见分布程序，产检的威布尔分布，瑞利分布，K分布等分布，采用语言为matlab。(Fitting a variety of common distribution procedures, check-Weibull distribution, Rayleigh distribution, K distribution of the distribution, the use of language matlab.)

信号处理与分析，是基于gui的信号处理与分析，相关函数的应用。(Random signal analysis and Process)

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 )

gabor变换程序，初学，matlab,写的比较简单。供大家参考。(gabor transform procedures, beginner, matlab, written in relatively simple. For your reference.)

一个简单的PID simulink控制倒立摆的模型建立(A simple PID simulink control of inverted pendulum model building)

说明：  matlab .M函数库，自己整理的，我用的很好，朋友们能参考一下(matlab. M library, his finishing, I use the good friends who can refer to)