work

describes Fourier Series representation of square wave signal.

this source code is matlab cctime

matlab振动信号处理工具包可以进行滤波，信号时频域转换，试验模态参数辨识，时间序列分析等功能(MATLAB vibration signal processing tool bag, filter, experimental modal parameter identification and time series analysis and other functions)

matlab 小波变换 有嵌入水印部分和提取水印部分(watermarking)

说明：  一种适用于感应电机的定子磁链优化的直接转矩控制技术。(One for induction motor stator flux-optimized direct torque control technique.)

多变量输入、输出、多干扰、非线性和强耦合的复杂系统控制是一个比较困难的问题，常用的控制器可能因为多变量耦合问题难以控制系统。PID神经元网络是一种多层前向神经元网络，它的各层神经元个数、连接方式、连接权值是按照PID控制规律的已有原则和经验确定的，是一种动态的符合控制系统的前向网络。但是由于PID网络初始权值随机取值的原因，每次控制的效果都有所差别，个别情况下控制效果还比较差。本案例研究了基于PID神经元的多变量耦合系统控制，并用PSO算法来优化控制器以取得更好的控制效果。(Multivariable input, output, and more interference, complex nonlinear and strong coupling system control is a more difficult problem, commonly used multivariable controller may be because the problem is difficult to control the coupling system. PID neural network is a multi-front to neural networks, its number of neurons in each layer, connection, connection weights are in accordance with the existing principles and experience to determine the PID control law is a dynamic compliance before the control system to the network. However, due to the random initial weights of the network PID values ​ ​ of reason, every time there are differences in the effect of control and in some cases the control effect is still relatively poor. This case study of multivariable coupling system based on PID control neurons, and with PSO algorithm to optimize the controller to achieve better control effect.)

NSIS NSIS图文教程集锦，方便大家做软件安装程序，有很多有用的小技巧(NSIS NSIS Photo Gallery tutorial, we facilitate a software installation program, there are many useful tips)

对于卫星编队飞行低推力构型重构机动的优化设计(Optimization of Low-Thrust Reconfiguration Maneuvers for Spacecraft Flying in Formation)

该代码利用BP_MIP算法实现数据挖掘中多示例机器学习方法中示例包的标记分类。(BP_MIP Using the BP-MIP algorithm to get the labels for bags in testBags)

用matlab实现的BP神经网络，比较基础，对已有的语音信号进行分类，留了500个作为检验(Using matlab to achieve the BP neural network basis of comparison, the existing classification of the speech signal, leaving a 500 as a test)