matlab_gjxhs

。本书首先讲述了MATLAB语言程序设计基础，然后分别介绍了符号计算在微积分和复变函数两门大学数学基础课程中的应用，接着系统的介绍了线性方程组、非线性方程与最优化方法、特征值与特征向量、插值与函数逼近、估计方法和数据拟合、积分计算、常微分方程的数值方法。从实用角度考虑，本书许多章节都给出了一些数值分析的应用范例，并在最后一章单独介绍了一些综合性较强的数学建模问题(This book starts by describing the basis of MATLAB programming language, and then introduced the symbolic computation in calculus and complex functions based on two college courses in applied mathematics, and then introduced the system of linear equations, nonlinear equations with the most optimization method, eigenvalue and eigenvector, Interpolation and function approximation, estimation and data fitting, integral calculation, numerical methods for ordinary differential equations. From a practical point of view, many of the chapters the book gives some numerical analysis are examples of the application, and separate in the final chapter describes some of the more integrated mathematical modeling)

The chebfun project is a collection of algorithms, and a software system in object-oriented Matlab, which extends familiar powerful methods of numerical computation involving numbers to continuous or piecewise-continuous functions. It also implements continuous analogues of linear algebra notions like the QR decomposition and the SVD. The mathematical basis of the system combines tools of Chebyshev expansions, fast Fourier transform, barycentric interpolation, Clenshaw-Curtis quadrature, and recursive zerofinding.

说明：  一种非线性流形学习和维度缩减的算法，可以用来对数据进行降维和数据可视化。(Locally Linear Embbedding)

说明：  一个很好的模拟退火反演算法程序，例子是地球物理重力反演(A good simulated annealing inversion procedure, example is the geophysical inversion of gravity)

filling an area between two curves

matlab codes for viterbi encoding

说明：  选择“BreastCancer”数据集，使用支持向量机(SVM)对其进行分类。作为对比，第一次对特征集直接进行支持向量机分类，第二次对特征集进行主成分分析法的特征提取后，再对特征提取后的特征集进行支持向量机分类。并且对比和分析了两次分类的结果。(The BreastCancer data set is selected and classified by Support Vector Machine (SVM). For comparison, the first time the feature set is classified directly by support vector machine, the second time the feature set is extracted by principal component analysis, and then the feature set is classified by support vector machine. The results of the two classifications are compared and analyzed.)

无约束多维极值问题,适合数学计算,优化分析等极值问题的求解(Unconstrained multi-dimensional extremum problem, is suitable for mathematical calculations, the extremum problems of solving optimization analysis, etc )

立体图像质量评价，文章以cyclopean image为核心构建算法。(Full-reference quality assessment of stereopairs accounting for rivalry)

Caracteristiques d une ligne ELECTRIQUE 2011