Dream

单一频率的正弦相关法动态测试系统的测试方法简单，不需要对系统进行辨识。只需要观察被测系统输出信号的相差和幅值变化。通过扫频的方法测量在不同的频率点下的幅值和相位变化。在工程应用中，只需要知道被测系统的相位变化在正常的范围内就可以视系统的动态性能正常。该仿真算法只是建立了一个模型。在实际运用时还需要变换测试信号的频率和周期。(A single frequency sinusoidal correlation method of testing dynamic testing system is simple, does not require system identification. Only need to observe the difference between the measured system output signal and amplitude change. Swept through the method of measurement points at different frequencies under the amplitude and phase changes. In engineering applications, only need to know the system under test changes in the normal phase it may be possible within the framework of the dynamic performance of the system to normal. The simulation algorithm is the establishment of a model. In the practical application of test signals also needed to change the frequency and periodicity.)

correlation matching using matlab it is a code used for match correlation a image in matlab software. using this we can a correlate an image.

jpeg图像编码的matlab实现，主文件为jpegdemo(jpeg image coding matlab implementation, the master file is jpegdemo)

7级级联H桥逆变器 多电平大功率电力电子 中高压无功补偿 变频器 matlab仿真模型(7 cascaded H-bridge inverter multi-level high-power electronic converter high voltage reactive power compensation)

说明：  新能源汽车设计和控制，开发该算法，可以解决汽车能量回收问题。(And new energy vehicle design and control)

Image Scaling transaltion rotation codes in matlab

基于新的交叉算子的全局与局部实数编码遗传算法GL-25(Global and local real-coded genetic algorithms based on parent-centric crossover operators)

说明：  介绍了非线性姿态的滤波方法，加性ekf以及乘性ekf等(Introduction of non-linear profile filtering method, the additive and multiplicative EKF EKF, etc.)

说明：  计算金属球体RCS的MATLAB程序. 就是教科书上金属球体RCS曲线计算的MATLAB程序.(RCS calculation of the metal sphere of MATLAB procedures. Is textbook metal sphere RCS curve calculated MATLAB program.)

基于扩展记忆的粒子群优化算法（Particle Swarm Optimization based on memory）(This paper combines SVM with improved PSO (Particle Swarm Optimization with Extended Memory, PSOEM) and then builds PSOEM-SVM forecasting model. The PSOEM searches the solution space intelligently and finds out the best one. Parameters in SVM are optimized by PSOEM, which implements automation of the parameter optimization avoiding the blindness of selecting parameters. Not only does it utilize the generalization feature of SVM, but enhance the global search ability of PSO (Particle Swarm Optimization). Thus, both accuracy and speed are increased at the same time.)