ch01_2ed

说明：  采用总变分法（TV）进行图像修复的matlab源代码。包括热扩散修复和多尺度方法。(using variational (TV) for image restoration of Matlab source code. Thermal diffusivity including repair and multi-scale approach.)

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)

分支定界法求解TSp问题的分析研究以及matlab实现(Branch and bound method to solve the problem described TSp)

此程序描述了基于梯度投影重建的稀疏方法切用matlab实现( This passage describes Gradient Projection for Sparse Reconstruction use matlab.)

matlab算法,可以实现一些基本的图像处理的算法，也可以进行图像分割(matlab )

一个锁相环路，同相正交环路，一阶锁相环，做毕业设计时遇到的。(A phase-locked loop, quadrature-phase loop, the first order PLL, the design experience to do graduate.)

The attached files provides a guidance to matlab newbie about digital image processing.

统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines( This section should give the reader a quick overview of the methods implemented in STPRtool. • Analysis of linear discriminant function: Perceptron algorithm and multiclass modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection of known algorithms solving the Generalized Anderson’s Task. • Feature extraction: Linear Discriminant Analysis. Principal Component Analysis (PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis. • Probability distribution estimation and clustering: Gaussian Mixture Models. Expectation-Maximization algorithm. Minimax probability estimation. K-means clustering. • Support Vector and other Kernel Machines: Sequential Minimal Optimizer (SMO). Matlab Optimization toolbox based algorithms. Interface to the SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers. Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell- Demyanov-Molozenov algorithm )

matlab学习教程，包括matlab软件基本操作以及对数据的处理，对图形的处理(matlab tutorial, including the matlab software and the basic operation of data processing, graphics processing)

说明：  对比capon和music算法的测向效果，music采用特征分解法，测向比Capone更准确(Comparison of capon and music finding algorithm results, music by feature decomposition method, finding more accurate than Capone)