springmass

MATLAB命令大全-matlab 命令使用指南(MATLAB command-matlab command Guinness Guide)

说明：  OFDM的QPSK仿真程序，里面只有一个txt文件，所有程序都在上面了。(OFDM QPSK simulation program, only a txt file, all proceedings in the above.)

matlab仿真bpsk的源代码，很有参考价值的(BPSK simulation matlab source code, are worthy of)

matlab绘图叙述了许多绘图的方法，对大家学习matlab有很大帮助。(matlab drawing method described in a number of drawings, all of us to learn matlab great help.)

This function computes the RMS feature of the signals in x,which are stored in columns. The signals in x are divided into multiple windows of size winsize and the windows are space wininc apart. Inputs x: columns of signals winsize: window size (length of x) wininc: spacing of the windows (winsize) datawin: window for data (e.g. Hamming, default rectangular) must have dimensions of (winsize,1) dispstatus:zero for no waitbar (default) Outputs feat: RMS value in a 2 dimensional matrix dim1 window dim2 feature (col i is the features for the signal in column i of x)

农田多标记小图，可以用以极化SAR分解和半监督极化SAR分类。(Farmland multi-label small map, can be used to polarimetric SAR polarimetric SAR decomposition and semi-supervised classification)

二维FDTD 实现电磁场的二维分析。源代码。可以为FDTD初学者提供便利(Two-dimensional FDTD to achieve two-dimensional electromagnetic field analysis. Source code. FDTD beginners can facilitate)

CDMA users BER analysis

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.)

基于matlab，运用差值和拟合的方法进行模拟，最后绘图(Based on matlab, the use of difference and the fitting method of simulation, the last drawing)