BregmanCookbook_v32

MIT-BIH心电数据库中包含有大量的心电信号，用户可以直接下载这些信号用于信号分析，算法验证等。但是其数据存储格式复杂，只能用其提供的工具包进行读取，很不方便。本源码可以直接读取MIT-BIH中的format212和format16格式的心电数据，免去了学习其繁琐工具包的过程。(MIT-BIH ECG database contains a large number of ECG signals, users can directly download these signals used in signal analysis, verification algorithm. However, the complexity of its data storage format, can only provide a toolkit to read, very inconvenient. The source can be directly read the MIT-BIH in format212 and format16 ECG data format, which eliminates the cumbersome tool kit to learn their process.)

计算指数平滑模型预测及预测值与真实值的统计量计算(Exponential smoothing model and prediction value statistic calculation)

采用M语言对一正弦信号实现基于卡尔曼滤波器的PID控制(PID control based on kalman filter)

说明：  利用随机方法产生-1 +1 分布的白噪声(using random methods-1 1 distribution of white noise)

模式分类这本书的被套的工具书，包含有各种分类的算法的MATLAB的代码实现，《Computer+Manual+in+MATLAB+to+Accompany+Pattern+Classification+2nd+Edition》(pattern recognition and useness with matlab code tools)

基于电流滞环的FOC PMSM 仿真模型。测试通过(Hysteresis based on the FOC PMSM current simulation model. Test)

有关工频噪声的滤波算法的算法实现，分别用C语言和Matlab语言(you guan gongpin zaosheng de lv bo suanfa de suanfa shijian fenbie yong C and Matlab)

这是一个为友人所写的小程序, 实现了分段模糊查询, 网页生成等小功能! (This is a small program written by a friend, realize a sub-fuzzy query, the page to generate small features!)

GMDH_main为GMDH主函数； variable_Combin为输入层初始变量选为x1,x1^2,x1*x2,x2^2,x2时的输入变量矩阵值 variable_select计算X_train训练输入数据,Y_train训练输出数据,X_test测试输入数据,Y_test测试输出数据 Combin为求变量的两两组合 Sym_Combin为求符号变量的两两组合 PE_AIC求每层各神经元的参数估计W，及训练数据在参数估计后估计的输出out_train，测试数据在参数估计后的估计输出out_test，还有与实际比较的误差平方和PESS， 以及准则值AIC sym_representation求最终的输入输出符号表达式 Criterion_value求准则值 (GMDH_main main function for the GMDH variable_Combin initial variables chosen for the input layer, x1, x1 ^ 2, x1* x2, x2 ^ 2, x2 the value of the input variable matrix calculation X_train variable_select training input data, Y_train training output data, X_test test input data, Y_test for the sake of the test output data Combin pairwise combination of variables for the sake of symbolic variables Sym_Combin pairwise combinations PE_AIC neurons find each parameter estimation of the W, and after the training data is estimated in the estimation of output out_train, test data After the parameter estimates of the output estimated out_test, also compared with the actual sum of squared errors PESS, as well as the final criterion value AIC sym_representation seek the input and output values ​ ​ of symbolic expressions Criterion_value find criteria)

说明：  双电机模型用于汽车的搭载和嵌入，与其他汽车模型联合使用(The dual motor model is used for vehicle loading and embedding, and is used in combination with other vehicle models)