sift 图像处理

图论中的最大流matlab应用程序，非常好用！(Graph theory of maximum flow matlab application, very easy to use!)

This demo tracks cars in a video by detecting motion using optical flow. The cars are segmented from the background by thresholding the motion vector magnitudes. Then, blob analysis is used to identify the cars.

非常快速的稀疏编码求解过程。可以用于各种类型的数据(fast solving the problem of sparse coding.You can apply sparse coding to any type of general data.)

说明：  这实际是一个通用的旋转正交经验函数。采用Kaiser标准化(Rotate EOF's This is actually a generic varimax routine and knows nothing special about EOFs. It expects a matrix of "loadings")

说明：  谐波小波滤波再加上随机减量，谐波小波相当于带通滤波器，效果很好(Coupled random harmonic wavelet filter reduction, harmonic wavelet is equivalent to band-pass filter, the effect is very good)

三点二次差值搜索法，基于折线法的信赖域算法。(Three-point quadratic difference search method, trust region algorithm based on the fold line.)

Example of using huge page memory in a user application using the mmap system call.

MATlab30个案例分析 第11章 流水车间调度的遗传算法MATlab实现(Analysis of MATlab30 cases Chapter 11 Flow Shop Scheduling the genetic algorithm MATlab achieve)

利用泊松方程得到PN结热平衡下的电势分布(Poisson equation PN junction thermal equilibrium electrical potential distribution)

（压缩包里一共有5个代码） pca+lda+粗糙集+模糊神经网络 saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat 1.savelda.m将人脸库先进行pca降维，再用lda进行特征提取，得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat 2.对ldastudy进行离散化(discretimage.m)，得到离散化矩阵disdata,存入到imagedisdata.mat 3.将disdata组成决策表(savers.m)，通过对disdata的条件属性进行约简，得到其一个约简，组成新的测试集rstest和训练集rsstudy存为imagersdata.mat 4.对rsstudy进行模糊神经网络训练(savecul.m)，对模糊神经网络的参数进行调整学习将其存入culdata.mat 5.用runfnn.m对rstest进行测试得到其识别率 savem.m和cm.m是用最小距离分类器对训练集和测试集进行分类.(pca+ lda+ Rough Set+ fuzzy neural network saveORLimage.m will ORL face database is divided into test set and training set ptest for pstudy keep imagedata.mat Treasury will face 1.savelda.m first dimensionality reduction pca, lda used feature extraction, a new test set and training set ldatest for ldastudy keep imageldadata.mat 2. Ldastudy carried out on the discretization (discretimage.m), to be discrete matrix of disdata, deposited to imagedisdata.mat 3. Disdata the composition of the decision table (savers.m), the conditions on the attributes disdata about Jane, has been one of its reduction to form the new test set and training set rstest for rsstudy keep imagersdata.mat 4. Rsstudy training fuzzy neural network (savecul.m), on the parameters of fuzzy neural network to learn to adjust their deposit culdata.mat 5. Rstest used to test for runfnn.m by its recognition rate cm.m is savem.m and minimum distance classifier on the training set and test set classificati)