MinimumCostFlow

基于KPCA_SVM的柴油机状态识别方法的研究 把KPCA与SVM共同用到柴油机状态识别中(KPCA_SVM based on the state of the diesel engine study to identify methods of KPCA and SVM to identify the common use of diesel engine state)

我自己编写的平均功率分配下，SISO信道为复高斯信道的信道容量程序，matlab(I have written under the average power distribution, SISO channel is complex Gaussian channel capacity channel program, matlab)

说明：  使用Fisher 现行判别函数对给定的样本进行训练，对于两类，Fisher线性判别函数很好做，就是 w = Sw (m1 - m2), 其中：Sw为总类内离散度矩阵， m1, m2, 为两个模式类的均值(Fisher discriminant function using the current sample of a given training for two, Fisher linear discriminant function is well done, that is, w = Sw ' (m1- m2), where: Sw of the total within-class scatter matrices, m1, m2, the mean value for the two pattern class)

此MATLAB文件专门用于求某个顶点到其他顶点的最短距离(This MATLAB file dedicated to seeking the shortest distance of a vertex to other vertices)

该程序是对飞行器的航迹进行模拟。包括3个文件，主程序是fangzhen.m，可以反映出飞行器高度、速度、攻角等参数对飞行器航迹的有效(The program is a simulated aircraft track. Includes three files, the main program is fangzhen.m, can reflect the aircraft altitude, speed, angle of attack of the aircraft trajectory parameters are valid)

说明：  matlab 仿真小程序集合,欢迎大家使用(matlab simulation package)

Custom tools for MATLAB supporting analysis and design of nonlinear control systems are introduced in this paper. The paper demonstrates their use to solve sample nonlinear control problems and presents some of the MATLAB algorithms involved

BTC compression code

Dennis M.Sullivan FDTD书后matlab程序 已经调试验证 第四章(Dennis M.Sullivan matlab program using FDTD book have been debug and verify)

The early detection of arrhythmia is very important for the cardiac patients. This is done by analyzing the electrocardiogram (ECG) signals and extracting some features from them. These features can be used in the classification of different types of arrhythmias. In this paper, we present three different algorithms of features extraction: Fourier transform (FFT), Autoregressive modeling (AR), and Principal Component Analysis (PCA). The used classifier will be Artificial Neural Networks (ANN). We observed that the system that depends on the PCA features give the highest accuracy. The proposed techniques deal with the whole 3 second intervals of the training and testing data. We reached the accuracy of 92.7083 compared to 84.4 for the reference that work on a similar data.