fitellipse

DLP 投影仪开发手册，作为结构光投射设备，可以达到实时重建的功能(DLP Projector Development Manual, as structured light projection apparatus, can achieve real-time reconstruction of functional)

结构光重建MATLAB模拟代码，采用PMP原理(MATLAB simulation code for structural light reconstruction)

测试Glew开发环境搭建是否成功，如果您成功的安装了对应的glut和glew库文件。(the test code for glew, to know is it working.)

小波基的构造，每步均有说明，讲解很详细，值得学习(Wavelet construction, each step that has to explain in great detail, it is worth learning)

运用微粒群算法求解改进的二维熵最大值算法，对于医学图像分割非常有用(Using the PSO algorithm to calculate the maximum of the improve 2D entropy value)

本程序是基2的时间抽取FFT变换，可以将信号从时域转换到频域。(This procedure is the base 2 time extraction FFT transform, can transform the signal from time domain to frequency domain.)

利用matlab进行图像数据的剪裁，需要提供需剪裁影像的中心点行列号；RMSE.m是计算均方根误差RMSE的程序。(Using MATLAB to tailor the image data, we need to provide the central point and row number of the image to be tailored. RMSE.m is a program to calculate the root mean square error RMSE.)

主成分分析 （ Principal Component Analysis ， PCA ）或者主元分析。是一种掌握事物主要矛盾的统计分析方法，它可以从多元事物中解析出主要影响因素，揭示事物的本质，简化复杂的问题。计算主成分的目的是将高维数据投影到较低维空间。给定 n 个变量的 m 个观察值，形成一个 n ′ m 的数据矩阵， n 通常比较大。对于一个由多个变量描述的复杂事物，人们难以认识，那么是否可以抓住事物主要方面进行重点分析呢？如果事物的主要方面刚好体现在几个主要变量上，我们只需要将这几个变量分离出来，进行详细分析。但是，在一般情况下，并不能直接找出这样的关键变量。这时我们可以用原有变量的线性组合来表示事物的主要方面， PCA 就是这样一种分析方法。(Principal component analysis (Principal Component Analysis, PCA) or PCA. Is a statistical method to grasp the principal contradiction of things, it can be resolved diverse things out the main factors, revealing the essence of things, simplifying complex problems. The purpose of calculating the main component of high-dimensional data is projected to a lower dimensional space. Given n variables of m observations, forming an n ' m of the data matrix, n is usually large. For a complex matters described by several variables, it is difficult to know, so if you can grab something to focus on key aspects of analysis? If the main aspects of things just reflected on several key variables, we only need to separate out these few variables, for detailed analysis. However, in general, does not directly identify this critical variables. Then we can represent the major aspects of things with a linear combination of the original variables, PCA is one such analysis.)

基于keystone变换校正距离走动的机载预警雷达高速运动目标动目标检测方法(High-speed moving target moving target detection method based on keystone correction transformation walking distance airborne early warning radar)

08年新的Delaunay程序，很不错的！(Delaunay new 2008 program, it is good!)