PIDcalc

异步电动机状态方程模型，使用matlab S函数(asynchronis machine state equation model, using matlab S-function)

利用matlab设计FIR低通滤波器和IIR低通滤波器。编译通过。(matlablowpass filter)

基于 BP 神经网络的高压潜水电机绝缘寿命预测,俺是初学者，这是花钱下载的，比较前沿，希望对各位有用。(High Voltage Submersible Motor Insulation Life Prediction Based on BP Neural Network )

matlab实用程序百例(100 cases of matlab utility)

通信系统中实现幅度调制与解调。用matlab方式实现。(Communication systems to achieve amplitude modulation and demodulation. Way to use matlab.)

RS分形算法matlab代码实现,既利用RS方法计算时间序列的分形hurst指数(RS fractal algorithm to achieve Matlab code, RS is calculated using time series fractal hurst index)

元胞自动机中Conway s life 程序模拟系统，根据所需步数来确定模拟结果，用MATLAB图形界面（GUI）实现。(Conway' s life cellular automata program simulation system, based on the number of steps required to determine the simulation results, implemented using MATLAB graphical interface (GUI).)

自己写的快速傅里叶变换，处理N点数据的傅里叶变换，含两个MATLAB的M文件,可直接使用(Fast Fourier Transform, write your own data of the N-point Fourier transform, containing two MATLAB M-files can be used directly)

binary frequency division multiplixing

：压缩感知是近年来应用数学界提出的一套关于稀疏信号采集和重构的新理论，它突破了传统奈奎斯特采样定理 的限制，以远少于传统奈奎斯特采样定理所需的测量数据就能够精确恢复原信号或估计信号的相关参数。将压缩感知理论应 用到DOA估计，可以解决传统DOA估计中高采样率、以及较多辐射源信号条件下难以定位的限制。研究了基于压缩感知理 论的DOA估计方法，并利用MATLAB进行仿真，通过与传统MUSIC算法比较可知，基于压缩感知的DOA估计方法具有显著 的优势(The theory of Compressive Sensing(CS)is the application of mathematics in the field of a sparse signal acquisition and reconstruction of the new theory. It breaks through the traditional limitation of Nyquist sampling theorem. It can recover certain signals or estimate their parameters far fewer samples or measurements than traditional methods. The application of compressed sensing theory to DOA estimation can solve the traditional DOA estimation in high sampling rate, as well as more of the radiation source signal conditions is difficult to position limits. This paper studies the theory of DOA estimation method based on compressed sensing theory, and simulation uses MATLAB, compared with the traditional MUSIC algorithms, DOA estimation based on compressed sensing theory method has the obvious advantage)