coding

S函数实现PID的算法，包含离散形式的算法实现，和连续形式的算法实现。(Using PID to achieve S-Function algorithm)

说明：  How to implement NOMA system

tan function to sin and cosine

introduction to matlab part 1 with example

空间后方交汇求解相机外方位元素，变量如下 ％ x，y 控制点像点坐标 ％ X，Y，Z 控制点空间坐标 ％f焦距 ％X0，Y0，Z0，a，b，c六个外方位元素 ％x0，y0，-f内方位元素：光心坐标 ％cha，chb，chc：外方位角元素改正数 ％count 记录迭代次数 ％R 旋转矩阵 ％A 线性化的偏导系数矩阵 ％L 常数项矩阵 ％M0 外方位元素矩阵 ％M1 外方位元素改正数矩阵(meeting space for rear camera position outside elements, as follows% variable x, y control point pixel coordinates% X, Y, Z coordinates control room focal length f%% X0, Y0, Z0, a, b, c 6 exterior orientation elements% x0, y0,- f position within elements : Optical Center coordinates% cha, chb, chc : Foreign elements azimuth correction% record count the number of iterations rotation matrix R%% A linear partial derivative of the coefficient matrix% L constant Matrix% M0 Orientation% M1 matrix elements of exterior orientation correction matrix)

利用tol和bol进行多基地的定位，最后给出GDOP图(TOL and BOL are used to locate for multi base, and finally the GDOP diagram is given)

sourceRadar.m 产生雷达数据 sourceIR.m 产生红外数据 EKF_Radar.m 雷达数据扩展卡尔曼滤波 EKF_IR.m 红外数据滤波 Asynchronism_Radar.m 雷达数据同步 Asynchronism_IR.m 红外数据同步 fusion_asyn.m 异步数据融合(sourceRadar.m produce radar data sourceIR.m radar data to produce infrared data EKF_Radar.m extended Kalman filter EKF_IR.m infrared data filtering Asynchronism_Radar.m Asynchronism_IR.m infrared radar data synchronization data synchronization fusion_asyn.m asynchronous data fusion)

基于matlab实现对一维信号的分解与重构，在信号处理中有相当的使用价值。(Matlab based on the realization of one-dimensional signal decomposition and reconstruction, in signal processing have considerable value.)

计算序列的DFT，并画出其幅度和频谱曲线(Computing the DFT of the sequence, and draw the magnitude and spectrum curve)

Generador de señ ales Seno y Coseno