demo_matladd

本程序用于进行平板裂纹扩展，模拟，分析，平板内气孔夹杂的分析，使用的方法为扩展有限元法（XFEM）,程序语言为MATLAB.(This procedure is used for the analysis of plate crack propagation, simulation, and analysis of void inclusion in a plate, using the method for the extended finite element method (XFEM), and the programming language for MATLAB.)

数值分析的EULER法，matlab开发工具箱中的支持向量机，预报误差法参数辨识-松弛的思想。( EULER numerical analysis method, matlab development toolbox support vector machine, Prediction Error Method for Parameter Identification- the idea of relaxation.)

帧内预测编码，已调试成功，垂直预测，其他预测方式可进行相应的修改(Intra prediction coding, debugging has been successful, the vertical prediction, other prediction methods can be amended accordingly)

暂时只支持jpeg2000支持的 cdf97 和spline53 可以这样来测试： x=imread( E:studyjpeg2000imageslena.tif ) ％ see the decomposition coefficients y=wavelift(x, 1, spl53 ) using spline 5/3 wavelet figure subplot(1,2,1) imshow(x) subplot(1,2,2) imshow(mat2gray(y)) ％ see the reconstruction precision yy=wavelift(x, 5) using cdf 9/7 wavelet ix=wavelift(yy,-5) inverse sum(sum((double(x)-ix).^2)) (only temporary support jpeg2000 support cdf97 and spline53 this can be measured Examination : x = imread (E : study jpeg2000 images lena.tif)% see the d ecomposition coefficients wavelift y = (x, 1, spl53) using spline 5/3 wavelet figure subplot (1,2,1) imshow (x) subplot (1,2, 2) imshow (mat2gray (y))% see the reconstructi on precision wavelift yy = (x, 5) using cdf 9/7 wavelet ix = wavelift (yy.-5) inverse sum (sum ((double (x)- ix). ^ 2)

最速下降法，基於matlab開發環境，可用於求解優化問題(The steepest descent method, based on matlab development environment can be used to solve optimization problems)

很多经典的粒子群算法的matlab程序，智能计算方面的(Many classical PSO algorithm matlab procedures, intelligent computing)

实现三阶谱估计也就是双谱估计的一个实例，可以用于信号处理领域。(This is a routine about the bispectrum estimation, you can use it to process the signal so that u can get some features about it.)

先进PID控制方法的matlab仿真刘金坤编著有编好的程序很有用 (Advanced PID control method for a matlab simulation program has made very good use)

This file find the best coordination for a data set to reduce its dimension. Large data set,Dimension Reduction.

work with 3d grafic in matlab