MATLAB

用趋近律方法设计的滑膜控制器算法例程，模型对象为G(s)=133/s(s+25).(Reaching law designed by synovial controller algorithm routines, model objects for the G (s) = 133/s (s+25).)

针对由于抖动和环境干扰造成的拍摄影像模糊问题，利用维纳滤波法进行图像恢复(As for the environmental disturbance caused by jitter and image blur shooting problems, the use of Wiener filtering method for image restoration)

基于核方法的主成分分析matlab源代码，比较经典，推荐学习。(Method based on kernel principal component analysis matlab source code, more classic, recommended learning.)

DC motor selection via torque calculation

This file is simulation of PSS in matlab simulink. This file is helpful for understanding POWER SYSTEM.

说明：  LMS/F组合算法由Shao-jen Lin和J.G.Jarris提出，它计算量增加不多却同时兼有LMS和LMF算法的优点。即收敛速度和稳态性能比基本LMS算法好，稳定性比LMF算法好。(LMS/F combination algorithm by the Shao-jen Lin, and JGJarris proposed, it is increasing much more calculations with both LMS and the LMF of the method. Ie, the convergence speed and steady-state performance better than the basic LMS algorithm, stability, better than the LMF algorithm.)

模拟2个独立窄带信号入射到均匀线阵上，信号间互不相关，与噪声相互独立，噪声为理想高斯白噪声，阵列的阵元数为10，快拍数为200。阵元间距为入射信号波长的1／2，信噪比为20dB，信号入射角度差分别为5°，10°，20°。(Simulate two independent narrowband signals incident on the ULA, among signal unrelated, independent noise, the noise is ideal Gaussian white noise, the number of array elements of the array is 10, the number of snapshots to 200. Element spacing is 1/2 of the wavelength of the incident signal, SNR is 20dB, the signal difference between the angle of incidence was 5 °, 10 °, 20 °.)

说明：  lagrange的M文件，在数学最优问题中，拉格朗日乘数法（以数学家约瑟夫·路易斯·拉格朗日命名）是一种寻找变量受一个或多个条件所限制的多元函数的极值的方法。(M file of Lagrange,In mathematical optimal problems, Lagrange multiplier method (named after mathematician Joseph Louis Lagrange) is a method to find the extremum of multivariate functions whose variables are limited by one or more conditions.)

demo maltab PRLQG - control theory

产生16路信号，画出16路原始信号的频谱叠加图以及滤波器响应，并画出结果信号的时域和频域波形(Generate 16-channel signal, draw 16 original signal spectrum overlay and a filter response, and draw result signals in time domain and frequency domain waveforms)