jiandanronghe

说明：  图像配准，利用互信息进行图像配准，主要针对旋转和平移(Image registration using mutual information for image registration, the main response to rotation and translation)

一种用三维重建的matlab代码，有实验结果图(A three-dimensional reconstruction of the matlab code, with experimental results)

泰勒展开NURBS曲线插补算法,图文并茂。(nurbs)

说明：  使用MATLAB提取二值图像特征值，并对连通区域进行标记、分析与计算(MATLAB is used to extract the binary image feature values, and mark, analyze and calculate the connected area)

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.)

关于图形学的一个算法，主要实现了投影。比较适合初学者(An algorithm on the graphics, the main achievement of the projector. More suitable for beginners)

说明：  二维功率谱密度计算程序 使用傅里叶变换，可以计算功率谱密度(Two dimensional power spectral density calculation program using Fourier transform)

热电厂CAD图纸资料，在CAD软件中绘制(Thermal power plant CAD drawings)

说明：  基于bp神经网络的车牌识别，运行时先运行nn.进行训练(License Plate Recognition Based on BP Neural Network)

通过使用LLE PCA两种方法相结合的思路，提高人脸识别的分别率(LLE PCA by using the idea of combining two methods to improve face recognition rate difference)