matlab

图标编辑的源码，比较适合初学者进行分析。(Icon editor source code analysis is more suitable for beginners)

基于matlab 的贝叶斯算法，分类结果显示比较准确(Matlab-based Bayesian algorithm, more accurate classification results)

这是关于脑电信号预处理的程序，希望对大家有帮助(This is about the brain electrical signal preprocessing procedure, I hope it can help you)

相机坐标变换标定矩阵的张正友算法，用于标定相机图像坐标与世界坐标的关系(Coordinate transformation matrix camera Zhengyou calibration algorithm used to calibrate the camera image coordinates and world coordinates relations)

matlab数学手册，详细介绍了matlab的数学功能，适合数学类学生(matlab mathematics handbook, detailing the matlab mathematical functions for math class students)

说明：  针对一般的粒子群优化(PSO)学习算法中存在的容易陷入局部最优和搜索精度不高的缺点,对改进型PSO算法进行研究。由于惯性权重系数ω对算法是否会陷入局部最优起到关键的作用,因此,通过改变惯性权重ω的选择,对惯性权重系数采取线性减小的方法,引入改进型的PSO算法。采用改进的PSO算法对PID控制器进行参数优化并把得到的最优参数应用于控制系统中进行仿真。仿真实验结果表明:改进型PSO算法不会陷入局部最优,能得到全局最优的PID控制器的参数,并使得控制系统的性能指标达到最优,控制系统具有较好的鲁棒性。(Aiming at the shortcomings of general PSO learning algorithm, which is easy to fall into local optimum and low search precision, the improved PSO algorithm is studied)

说明：  并网逆变器下垂控制特性仿真，能正常仿真，波形控制输出有振荡，共学习参考使用。(droop control:The network-connected inverter sagging control characteristics simulation, can be normal simulation, waveform control output oscillation, a total learning reference use.)

This matlab code shows different trajectories developed by a 3 planar revolute robot. It contains the code to describe a flower, espiral, etc

为实现合成孔径雷达（SAR）图像分类算法的测试与评估，将VC/Matlab 混合编程技术应用到SAR 图像分类平台开发中，分析与 比较了4 种VC/Matlab 混合编程方法及各自优缺点，并着重研究了基于组件对象模型（COM）的VC/Matlab 混合编程方法。使用Matlab COM 编译器创建了SAR 图像分类算法组件，在VC 中调用其导出的接口函数。在此基础上，完成了SAR 图像分类平台的实例开发且 可脱离Matlab 环境运行。实验结果表明，该方法较好地发挥了VC 与Matlab 各自的优势，提高了SAR 图像分类平台开发的效率。(In order to test synthetic aperture radar （SAR） image classification algorithm，VC/Matlab mixed programming technology was used in SAR image classification platform development. Four VC/Matlab mixed programming methods were introduced and analyzed. Comparing with other three methods，the method based on component object model （COM） was studied particularly. SAR image classification algorithm component was created by Matlab COM complier，and its interface function could be invocated with VC. Using this method，a SAR image classification platform was realized. The platform could run without Matlab. The experimental result shows a good combination of VC and Matlab. So，developing efficiency could be enhanced a lot.)

Probability of symbol and bit error for M orthogonal signals