Jordan-Normal-Form

MATLAB中介绍简要的降低PAPR的pts编码方案，并给出了源码(Briefly described in MATLAB PAPR reduction coding scheme, and gives the source)

RGB to gray scale conversion of image.

最速下降法，基於matlab開發環境，可用於求解優化問題(The steepest descent method, based on matlab development environment can be used to solve optimization problems)

最短路径算法---数学建模中关于Matlab数学软件中的算法的程序matlab经典算法的程序Dijkstra(--- Mathematical modeling of the shortest path algorithm on the algorithm in Matlab mathematical software program classical algorithm matlab program Dijkstra)

这是常用的插值方法的matlab实现，包括拉格朗日插值、分段线性插值和三次样条插值，希望对大家有帮助。(It is commonly used in the interpolation method matlab realize, including Lagrange interpolation, piecewise linear interpolation and cubic spline interpolation, we want to help.)

这是中国科学技术大学的dsp实验内容，包括FFT，卷积，滤波器设计等内容，可供学习MATLAB以及深入理解dsp原理之用(This is dsp experiment of USTC, including FFT, convolution, filter design, etc., for learning MATLAB and in-depth understanding of the principle of dsp.)

以3*3为模板在一幅灰度图像中寻找像素值大于给定阈值的所有点(To 3* 3 as the template to look at a gray image pixel value is greater than a given threshold for all points)

基于matlab的有限元分析源程序，用于结构静力分析(Finite element analysis of source code based on matlab for structural static analysis)

用欧拉方法计算二阶常微分方法。。。。。。。。。。。(computing two order ODE by euler s method....................)

统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含： 1，Analysis of linear discriminant function 2，Feature extraction: Linear Discriminant Analysis 3，Probability distribution estimation and clustering 4，Support Vector and other Kernel Machines( This section should give the reader a quick overview of the methods implemented in STPRtool. • Analysis of linear discriminant function: Perceptron algorithm and multiclass modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection of known algorithms solving the Generalized Anderson’s Task. • Feature extraction: Linear Discriminant Analysis. Principal Component Analysis (PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis. • Probability distribution estimation and clustering: Gaussian Mixture Models. Expectation-Maximization algorithm. Minimax probability estimation. K-means clustering. • Support Vector and other Kernel Machines: Sequential Minimal Optimizer (SMO). Matlab Optimization toolbox based algorithms. Interface to the SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers. Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell- Demyanov-Molozenov algorithm )