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MATLAB基础及应用 于润伟编著，适用于初学者快速入门。(MATLAB Fundamentals and applications, suitable for beginners to get started.)

支持向量机(SVM)实现的分类算法源码[matlab](Support Vector Machine (SVM) classification algorithm to achieve source [matlab])

说明：  amplitude modulation in matlab

This m file reads the V1 files of strong motion, i.e. the raw format as recorded by the accelerographs. Then seperates the three components, and puts the earthquake and station specifications into branches of a structure variable.

说明：  利用matlab软件编写的格子玻尔兹曼方法模拟的圆柱绕流问题，并实现了可视化(The flow around the cylinder is simulated by lattice Boltzmann method compiled by MATLAB software, and the visualization is realized)

求信号功率谱密度的简单程序，并将结构保存成TXT文档(Demand signal power spectral density of simple procedures, and to save the structure into a TXT document)

这是一个关于商人visit许多城市，怎样走法才能使距离最短的例子，采样的了退火算法的经典案例(Traveling Salesman Problem (TSP) has been an interesting problem for a l me in classical optimization techniques which are based on linear and nonlin ogramming. TSP can be described as follows: Given a numberof cities to v d their distances from all other cities know, an optimal travel route has to und so that each city is visited one and only once with the least possible dista aveled. This is a simple problem with handful of cities but becomes complica the number increases.)

Denmark Technical University的大牛Hansen，第二版风力机空气动力学。(Denmark Technical University' s Daniel Hansen, the second edition of wind turbine aerodynamics.)

自适应（LMS）算法在噪声抑制中的应用。在仿真中，原始信号选为sin((0.2*pi)*t), 噪声信号采用标准白噪声，延迟D=1，收敛因子分别是u=0.001和u=0.3(Adaptive (LMS) algorithm in noise suppression application. In the simulation, the original signal is selected sin ((0.2* pi)* t), noise signal using the standard white noise, the delay D = 1, respectively, convergence factor u = 0.001 and u = 0.3)

二次规划师非线性优化中的一种特殊情形，它的目标函数是二次实函数，约束函数都是线性函数。由于二次规划比较简单，便于求解（仅次于线性规划），并且一些非线性优化问题可以转化为求解一些列的二次规划问题，因此二次规划的求解方法较早引起人们的重视，称为求解非线性优化的一个重要途径。二次规划的算法较多，本文仅介绍求解等式约束凸二尺规划的拉格朗日方法以及求解一般约束凸二次规划的有效集方法。(Quadratic nonlinear optimization planners in a special case, its real objective function is a quadratic function, constraint functions are linear functions. Because of quadratic programming is relatively simple and easy to solve (after linear programming), and some non-linear optimization problem can be transformed into solving quadratic programming problems some columns, solving quadratic programming method therefore attracted attention earlier, saying an important way for solving nonlinear optimization. More quadratic programming algorithm, this paper describes only two feet Solving the Equality Constrained Convex Programming effective Lagrangian method and set method for solving general constrained convex quadratic programming.)