03CH4_red19

利用元胞自动机以及蒙特卡洛法模拟晶粒生长、凝固相变的一些源程序，以及对两种方法的一些简单文字介绍(The use of cellular automata and Monte Carlo simulation of grain growth, solidification phase change some of the source code, as well as two methods some simple text description)

这是一个用FDTD算法计算二维导体方柱散射场RCS的matlab程序.采用UPML吸收边界条件和高斯脉冲源激励,对于学习FDTD方法中的激励源加入,近-远场外推,吸收边界设置等很有帮助(This is a FDTD algorithm using two-dimensional square cylinder conductor scattering RCS of the matlab program. UPML absorbing boundary conditions used and the Gaussian pulse source excitation, the FDTD method to study the excitation source join, near- far outside the push, absorbing boundary settings, such as helpful)

利用QS4算法解决N皇后问题，解决300万的皇后所需时间在5s左右，特别快(Use QS4 algorithm to solve the N-queens problem, solve 3000000 Queen the time required for about 5s, particularly fast)

扩展有限元的Fortran代码，用于扩展有限元的数值仿真计算(Extended finite element of the Fortran code for the extended finite element numerical simulation.)

说明：  线性判别分析（LDA，全称Fisher Linear Discriminant Analysis）算法的C#实现源码，根据stprtool box for matlab中的LDA.m编写。用到MathNet库做相关的矩阵运算，使用zedgraph控制绘图。有简单的测试数据。( C# source code of linear discriminant analysis (LDA, full name of the Fisher Linear Discriminant Analysis) algorithm , according to LDA.m of stprtool box for matlab . Use MathNet library to do matrix operations,and use zedgraph control for drawing. Thers has a simple test data.)

最小二乘法(LS)仿真三个参考节点定位一个定位节点，包括仿真参数和过程数据收集(Least squares (LS) simulation of three reference nodes positioning a positioning node, including the simulation parameters and process data collection)

已经调试成功.内含m文件，可直接运行，迭代自组织数据分析，仿真图是速度、距离、幅度三维图像。( Has been successful debugging. M contains files can be directly run, Iterative self-organizing data analysis, FIG simulation speed, distance, amplitude three-dimensional image.)

利用下载的goce原始数据，计算得出含有时间/经纬度/重力梯度格式的程序(Use downloaded goce raw data, calculated with the time/latitude/gravity gradient program formats)

fractal compression using wavelet

基于贝叶斯-KNN文本分类算法的设计与实现。 是贝叶斯和ＫＮＮ两种分类算法的结合。(Bayesian-KNN text categorization algorithm design and implementation. Bayes and KNN is a combination of two kinds of classification algorithms.)