Remove_thenoises_using_wavelet_transform

最大熵法与Welch法估计的功率谱的比较。 多信号分类法估计的功率谱。 (Maximum entropy method and Welch' s power spectrum estimation comparison. Classification of multi-signal power spectrum estimate.)

几个常用通信和雷达信号的matlab仿真，包括bpsk,qpsk,qam和线性调频信号（2个）(Several commonly used communications and radar signals in matlab simulation, including bpsk, qpsk, qam and linear FM signals (2))

该文件可以让您的c从入门到真正的精通（在supn中）(from this file,you can learn a lots about c program in uspn)

BASICS OF ELECTRIC CIRCUIT FOR ELECTRICAL ENGINEERING STUDENTS

灰度图像的位面图程序 matlab环境下写的 希望能有帮助(Gray image Bit plane map program, hopes to help you)

基于PSO方法的PID参数整定，代码实用，适合初学者使用(PID parameter tuning based on PSO method, the code is practical, suitable for beginners to use)

this is code program to explain how to henon map chaos work

用Matlab实现四种混沌调频信号并画出其功率谱图(make four chaotic frequency modulation signal and its power spectrum plotted on a graph)

基于有限元法求解二维边值问题的matlab程序(Based on the finite element method of two-dimensional boundary value problem matlab program)

1.CAmodelfusion.m 主要功能： （1）完成两个传感器各自对基于CA模型的目标状态的Kalman估计； （2）实现传感器的局部状态估计的SCC和CI融合算法的实现； （3）画出局部估计和两种融合估计的位置、速度、加速度的误差； （4）画出局部估计和两种融合估计的协方差椭圆。 2.CVmodelfusion.m 主要功能： 功能与CAmodelfusion.m基本相似，差异在于实现基于CV模型的估计和估计融合。 3.CovInter.m 主要功能： 寻找CI融合算法的融合估计的协方差阵的行列式最小的权值。 4.f_plot_ellipse_m.m 主要功能： 绘制四种估计的协方差椭圆 (1.CAmodelfusion.m main functions: (1) completion of two sensors each target state based on CA model of Kalman estimation (2) the realization of the sensor partial state estimation algorithm SCC and CI integration and (3) Draw Local estimated position and two fusion estimation, velocity and acceleration errors (4) Draw two fusion of local estimates and estimated covariance ellipse. 2.CVmodelfusion.m Main Features: a CAmodelfusion.m similar, the difference is that the estimated CV-based estimation and model integration. 3.CovInter.m main functions: Find fusion algorithm fusion CI estimated covariance matrix of the determinant minimum weight. 4.f_plot_ellipse_m.m main functions: Draw four kinds estimate covariance ellipse)