shun-series

说明：  轧制力拟合程序 基本思想是线性方程加BP补偿(Fitting procedures for rolling force basic idea is to increase BP compensation of linear equations)

neural network toolbox的几个范例(BP, peceptron)(a few useful samples on neural network toolbox (BP, peceptron))

说明：  基于MATLAB单神经元PID控制源程序(MATLAB-based single neuron PID control source)

Important document and scripts from matlab about power electronics.

说明：  现代控制理论实验课 matlab倒立摆仿真代码和动画演示 使用matlab的倒立摆建模和仿真设计 使用了状态反馈控制器设计闭环反馈控制系统 实现了动画演示 文档说明：（中文字符显示某些问题，后续更改，系统的simulink构建很简单，这里没有注意到） 系统分析文件夹 .m输入为加速度的情况下的开环系统.m文件 F .m输入为力开环系统的m文件 State_FeedBack_controller.m输入为加速度的闭环系统的m文件 动画演示文件夹 sys.m生成整个控制系统的s函数 pendan.m显示动画的s函数 dh.mdl最终的动画倒立摆simulink的建造(Modern control theory experiment course Matlab inverted pendulum simulation code and animation demonstration Modeling and simulation design of inverted pendulum using MATLAB The closed-loop feedback control system is designed by using the state feedback controller The animation demonstration is realized Document description: (some problems of Chinese character display, subsequent changes, the system's Simulink construction is very simple, not noticed here) System analysis folder Open loop system. M file with. M input as acceleration The input force of the open loop F.M system State_ FeedBack_ The controller. M input is the m file of the closed loop system with acceleration Animation folder Sys. M generates the s function of the whole control system Pendan. M s function for displaying animation dh.mdl The construction of the final animation inverted pendulum simulink)

广义平稳非相关散射模型的MATLAB程序实现(Sense stationary uncorrelated scattering model of the MATLAB program realization)

采用互功率谱的方法进行生源定位仿真，并得到仿真结果(Using cross-power spectrum method of positioning the simulation students, and get the simulation results)

THIS FILE IS PART OF THE OggVorbis SOFTWARE CODEC SOURCE CODE.

Design of On-Line Nonlinear Kinematic Trajectory Tracking Controller for Mobile Robot based on Optimal Back-Stepping Technique

这个程序是在MATLAB下运行，对图像进行边缘检测。(This program is carried out on the image edge detection.)