bpr

Matlab入门经典教程--百看不厌.rar。。。。。。。。。(Getting Started Tutorial Matlab Classic- never lost their appeal. Rar. . . . . . . . .)

threshold for sparse approximation

用matlab编的俄罗斯方块游戏,实现该游戏各种功能(Matlab code of Tetris game with)

PDC齿测量齿面和齿侧的点确定切削齿的空间位置(cylinder circle norm line)

单摆的MATLAB仿真程序源代码，结果会输出单摆摆动画面。(Pendulum MATLAB simulation program source code, the result will be output pendulum swing screen.)

This program is used for simulation length and AR Model Wiener filtering

THIS IS A KOHENEN NEURAL NET TO RECOGNIZE CHARCTERS , TRAIN AND TEST PROGRAMS IN A SIMPLE WAY

Clustering 和 SVM 结合的预测模型算法。聚类采用k-means方法，SVM采用lib-svm工具箱。(kMeans and SVM(support vector machine) prediction model is provided.)

系统分析： O型控制系统的输出 在matlab上可以显示其输出图像(system analysis the graph of output in zero system )

Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.