MATLAB-wavelet

非常实用的基2DIT-FFT函数，直接运行可以分析原理。(Very practical base 2DIT-FFT function, operation can be analyzed directly principle.)

Kohonen的SOFM(自组织特征映射)源程序，希望大家喜欢(Kohonen's SOFM (self-organizing feature map) source hope you like)

书籍——[MATLAB从入门到精通].周建兴.清晰版.pdf(Books- [MATLAB from entry to the master]. Zhou Jianxing clear. Pdf)

说明：  libsvm用于matlab环境下，简小易用，速度非常快。(libsvm for matlab environment, simple small easy to use, very fast.)

Galerkin方法,这是一种真正的无网格方法.这种方法采用移动最小二乘函数采近似解变量,并且采用移动最小二乘近似函数的权函数作为加权残值法的权函数.文中对形成的离散动力学方程用Newmark方法求解(Galerkin method, this is a real meshless method. This method adopts moving least squares in function approximation solution variables, and adopts moving least squares approximate function of weight function as a weighted residual method of weight function. In the paper, the discrete dynamic equation formed with Newmark method to solve)

一系列关于信道仿真的基于Matlab的代码，相关的链路级仿真，十分详细(Series of channel simulation based on Matlab code, the associated link level simulation, very detailed)

电池全寿命加速老化试验的采集数据。在不同温度下的充电和放电下完成。数据格式为matlab的mat，文件里面有详细的实验数据说明，希望对研究电池寿命预测和诊断的同志有帮助。(Battery life-accelerated aging test data collection. At different temperatures to complete the charging and discharging. The data format is the matlab mat, which has detailed documentation of the experimental data shows that the hope of battery life prediction and diagnosis to help comrades.)

This is a simulink program for designing Low pass and High pass simple circuit Passive Filters

M=512 原图像长度 N=64 K=8 I=zeros(M,M) J=zeros(N,N) BLOCK=zeros(K,K) 显示原图像 I=imread( f:ceshiyuanshitu.bmp ) figure imshow(I) xlabel( 原始图像 ) 显示水印图像 J=imread( f:ceshilogistic_nuaa64.bmp ) figure imshow(J) xlabel( 水印图像 ) 嵌入水印 tem=1 for p=1:N for q=1:N x=(p-1)*K+1 y=(q-1)*K+1 BLOCK=I(x:x+K-1,y:y+K-1) BLOCK=dct2(BLOCK) if J(p,q)==0 a=-1 else a=1 end BLOCK(2,1)=BLOCK(2,1)*(1+a*0.01) BLOCK=idct2(BLOCK) I(x:x+K-1,y:y+K-1)=BLOCK end end 显示嵌入水印后的图像 figure imshow(I) xlabel( 嵌入水印后的图像 ) imwrite(I, f:ceshiembedded.bmp )

使用QR分解方法计算矩阵特征值的matlab源码(Calculated using the QR decomposition of the matrix eigenvalue matlab source)