DENOISING-OF-ECG-SIGNAL-HAVING-BASE-LINE-DRIFT

MATLAB实现能进行边缘检测，在生活中有很重要的应用(MATLAB implementation capable of edge detection, in life there are important applications)

在过阻尼情况下，典型二阶系统有两个相异的实数极点，其阶跃响应实际上是两个一阶系统响应的叠加。（ωn＝5），不断增大ζ值，观察每个ζ值下两个实数极点间的距离；同时绘出两个实数极点分别对应的一阶系统响应和二阶系统的响应，观察它们间的关系(In the overdamped case, the typical second-order system has two distinct real poles, and its step response is actually the superposition of the two first-order system response. (Wn = 5), increasing zeta values​ ​ , observing the distance between the two real poles each zeta value draw two real poles, respectively, corresponding to a first-order system response and the response of the second-order system, observe them relationship)

燃煤结渣预测，使用支持向量机与模拟退火算法进行优化参数(Slagging Prediction in coal boilers)

直接扩频通信是很重要的一种通信方式，他与卫星通信、光纤通信一并作为二十一世纪最伟大的发明，牛逼死了！(dsssDSSS is a very important form of communication, and satellite communication, optical fiber communication together as the greatest invention of the twenty-first century, died Niubi!)

可直接运行的基于拉普拉斯以及小波变换的多种融合方法的代码(Can be run directly based on the Laplace and the wavelet transform multiple fusion method code)

轨道交通领域，纽马克线性求解动力学微分方程(The field of rail transportation, the dynamic differential equations of linear Newmark)

MATLAB6.x符号运算及其应用.pdf 电子书，很不错的哦，学习Matlab的好资料！(Ebook MATLAB6.x Calculation and Use. It is Very good！)

matlab code min-max MLE

We have modified the leach algorithm to introduce effi cient cluster head replacement scheme and dual transmitting power levels

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)