matlab-process

说明：  主要是介绍卡尔曼滤波器的原理，并形象地说明了实现过程，最后用matlab实现了这一原理。(Mainly to introduce the principle of Kalman filter, and vividly illustrates the realization of the process, and finally use matlab to achieve this principle.)

说明：  sr的编程实现！！！在matlab的编程环境下实现！应用的蒙塔库塔算法！！(sr m a t l a b m a t l a b)

Paessens Algorithm for VRP

稀疏非负矩阵分解，稀疏非负矩阵分解（SNMF）在线形稀疏编码理论的基础上将大量数据分解成正稀疏分量的一种算法(SNMF，Sparse non-negative matrix factorization)

matlab 动画功能函数movie的演示程序(matlab movie demo)

绘制电容电压变化曲线 电阻、电感、电容串联电路R、L、C，试求电路突然接通电源E时，电源电压uc(t)的变化规律，并绘制R=1,L=0.5,C=1,E=1,uc（0）=0，uc’（0）=0时的电容电压uc(t)d 的变化曲线。 (Draw capacitance voltage variation curve resistor, inductor, capacitor series circuit of the R, L, and C, Find circuit suddenly turned on the power supply E, the variation of the supply voltage uc (t), and draw the R = 1, L = 0.5, C = 1, E = 1, UC (0) = 0, uc ' (0) = 0 when the capacitor voltage uc (t) is the change of d curve.)

三维FDTD的UPML吸收边界条件下的C程序(The three-dimensional FDTD UPML absorbing boundary C program)

MATLAB的应用可以遍及通信，信号处理等等，而MATLAB相关函数、命令则更是重要无比，掌握这些命令，对于我们学好MATLAB大有裨益。(MATLAB applications can throughout the communication, signal processing, etc., while the correlation function of MATLAB, the command is even more extremely important to master these commands great benefit for us to learn MATLAB.)

永磁同步电机模糊PID控制。含对比的PI控制的模型。实现了模糊控制算法，可以得到比单纯的PID更好的控制效果.(Fuzzy PID control of permanent magnet synchronous motor. Model PI-containing contrast control. Realization of fuzzy control algorithm can be better than a simple PID control.)

We address the problem of blind carrier frequency-offset (CFO) estimation in quadrature amplitude modulation, phase-shift keying, and pulse amplitude modulation communications systems.We study the performance of a standard CFO estimate, which consists of first raising the received signal to the Mth power, where M is an integer depending on the type and size of the symbol constellation, and then applying the nonlinear least squares (NLLS) estimation approach. At low signal-to noise ratio (SNR), the NLLS method fails to provide an accurate CFO estimate because of the presence of outliers. In this letter, we derive an approximate closed-form expression for the outlier probability. This enables us to predict the mean-square error (MSE) on CFO estimation for all SNR values. For a given SNR, the new results also give insight into the minimum number of samples required in the CFO estimation procedure, in order to ensure that the MSE on estimation is not significantly affected by the outliers.