Classification_toolbox

IDl语言编写的用于不同格式批处理转换，很实用(format conversion format conversion)

为全国大学数学建模爱好者提供matlab应用平台基础，主要内容是数学建模。(For lovers of the National University of mathematical modeling matlab application platform based on the main contents of the mathematical modeling.)

对stoke 方程的非协调员的新型解法,效率高，求解时间段等特点(a new method for stoke equation)

加权余量法--配点法法求解一维扩散方程。参考书《Computational Techniques for Fluid Dynamics》(The weighted residual method- collocation method for solving one-dimensional diffusion equation. Reference book " Computational Techniques for Fluid Dynamics" )

本书以Matlab6.1版为基础，详细介绍了基本原理、操作、运算以及数据的可视化处理、二维三维图形绘制与修饰、数据处理、数值计算、符号计算、simlink仿真等。 (Book Matlab6.1 version, based on detailed basic principles, operations, computing and data visualization, 2D and 3D graphics rendering and modification, data processing, numerical computing, symbolic computation, simlink simulation.)

说明：  滞回曲线分析 计算能量耗散系数 滞回曲线的加载圈数(Press the Analyze button, and the hysteretic loop will be decomposed into separate loops, from which the hysteresis loop area, secant stiffness, equivalent viscous damping coefficient are obtained.)

此文件包含三个MATLAB程序，用于对线性系统AR模型的权向量估计：Kalman滤波估计，RLS和LMS，均为较常用的估计方法，并附有相应的仿真图(There are three programs in this files:kalman,RLS and LMS to pridict the victors of linear systems . These three wawys are common and useful in signal processing)

现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。(existing algebra feature extraction method using a majority of the peacekeepers, First images will be converted into one-dimensional vector, and then principal component analysis (PCA), Fisher Linear Discriminant Analysis (LDA), Fisherfaces audits principal component analysis (KPCA), and other selected characteristics, then use the appropriate classification for classification. Victoria against an excessive dimension method, calculation, covariance matrix is often inadequate singular matrix, a two-dimensional image feature extraction method, a small amount of covariance matrix is usually reversible, and the recognition rate higher.)

拉格朗日乘数法 ， 主要解决求多元函数条件极值的问题。任何一本《高等数学》，《多元微积分》的教材都会介绍(Lagrange multiplier method, mainly to address the requirements of multi-function conditions extremum. A " higher mathematics" , multivariate calculus textbooks will be introduced)

GM11适应范围.PDF文件；非常实用的GM11模型Matlab程序。C语言基础即可明白，无需多言(GM11 adaptation range. PDF file very useful GM11 model Matlab procedures. C programming language to understand, no need to say)