matlabexamples

MATLAB数字信号处理释义与实现（陈怀琛）第三版(MATLAB interpretation and implementation of digital signal processing (Chen Huaichen) Third Edition)

实现k维度的核密度估计，包含了点积核和常规核函数的实现(implement k-dimensional kernel density estimation， supports product kernels ，Gausiankernel 。)

E=input( enter the generator voltage: ) V=input( enter the infinite bus voltage: ) Gx=input( enter the reactance of generator: ) L1x=input( enter the line reactance: ) L2x=input( enter the line reactance: ) L3x=input( enter the line reactance: ) L4x=input( enter the line reactance: ) Pi=input( enter the input power: ) X1=Gx+L1x+((L2x*L3x)/(L2x+L3x))+L4x Pm1=E*V/X1 DO=asin(Pi/Pm1) A=((L2x*L3x)/(2*(L2x+L3x))) C=A B=((L3x/2)^2)/(L2x+L3x) X2=(Gx+L1x+A)+(L4x+A)+(Gx+L1x+A)*(A+L4x)/B Pm2=(E*V)/X2 X3=Gx+L1x+L2x+L4x Pm3=(E*V)/X3 DC=input( enter the fault clearing angle: ) Dm=(3.14-asin(Pi/Pm3)) a1=quad( sin ,DO,DC) A1=(Pi*(DC-DO)-Pm2*a1) a2=quad( sin ,DC,Dm) A2=Pm3*a2-Pi*(Dm-DC) if(A2>=A1) disp( the system is stable ) else disp( the system is unstable ) end Dcc=acos((Pi*(Dm-DO)-Pm2*(cos(DO))+Pm3*(cos(Dm)))/(Pm3-Pm2)) disp( critical clearing angle: ) Dcc

SFN MFN BER with Matlab

Its a matlab code for tracking moving objects

这是北经航天出版社出版的书籍：现代永磁同步电机控制原理及MATLAB 仿真(This is the book published by the North Aerospace Publishing House: modern permanent magnet synchronous motor control principle and MATLAB simulation)

LBM方法求解流体力学中的lid driven flow 问题。输入迭代次数，输出流场速度矢量分布图。(LBM method for solving fluid mechanics in the lid driven flow problems. Enter the number of iterations, the output flow velocity vector distribution.)

说明：  主要都是 MATLAB RBF网络算法，可以直接使用(There are thirteen chapters in this paper. They are mainly intelligent algorithms of MATLAB, which can be used directly.)

MATLAB编写，可以实现掌纹图像的边缘提取，基于小波模极大值边缘提取。(Image edge detection.)

QR码作为一种可高速、全方位识别的二维条码,已经在各行各业中得到了应用,并具有很大发展潜力.本文针对QR码图像的识别过程中可能遇到的图像噪声干扰、QR码占实际拍摄图像的一部分、倾斜、几何失真等问题进行了研究,提出了通过改进型中值滤波去除噪声,使用QR码符号特性定位并对倾斜图像进行旋转,对失真不严重的图像采用控制点变换和双线性插值方法进行几何校正.实验证明, 本文的方法简单有效, 可以用于提高条码的正确识别率.(As a high-speed, full identification of the two-dimensional bar code, QR code has been applied in all walks of life, and also has great potential for development. In this paper, aiming at QR code image recognition process may be encountered in noise interference, QR code accounting for the actual captured image just a part, slant, geometric distortion, and other issues have been studied, put forward through improved median filter to remove noise, use QR code symbol characteristics to locate and rotate the tilted image, distortion which is not serious use control-point transform and spatial bilinear interpolation method for geometric correction. The results show that this method is simple and effective, can be used to improve the QR code correct recognition rate.)