Linear-nonlinear-LS-article

用simulink构建模型，解非线性达芬方程 (Nonlinear Duffen equation with simulink)

迭代加权最小二乘法（IRLS） 本算法用于解决某些优化问题。(IRLS(Iteratively reweighted least squares) The method of iteratively reweighted least squares (IRLS) is used to solve certain optimization problems.)

matlab robotics toolbox sample

本程序是矩形波的产生。第零步定义了要产生的波形的所有特征参数，矩形波的持续时间WIDTH，矩形波的采样点数POINTS,载波频率为F0，这个频率的最终引入是便于使用RF频率发射波形。第一步包括产生矩形波，并将其调制到RF上，注意，产生的信号的持续时间是矩形波宽度的5倍，这样，总的采样点数就是5*POINTS。同时还应注意，如果要产生一个基带信号，必须设置T0=0.第二步是画出所产生矩形波的源代码。( This procedure is rectangle wave production. Step to produce stage defined the waveform of all characteristic parameters, the duration of the rectangle wave WIDTH, rectangle wave sampling POINTS POINTS, carrier frequency F0, this frequency for the ultimate introduction is easy to use RF frequency emission waveforms. The first step including generating rectangle wave, and modulated to RF, attention, produce the duration of the signal is five times the width of rectangle wave, so, overall sampling POINTS is 5* POINTS. Also, note that if you want to produce a baseband signals must set T0 = 0. The second step is to draw a rectangular wave generated by the source code. )

matlab的程序包，可以用来计算复杂网络的各种参数(This matlab program package can calculate parameters of the network)

matlab使用过程中经常会使用到的常用数值算法。(often use to matlab the process of using the numerical algorithm.)

和先前传的程序是配套的，二者对比着看，有好处，可以更深的理解和应用(Chuan previous procedures are complementary, the two contrast look forward to, good, can be a deeper understanding and application of)

该程序是包含多种角点提取的方法，如harris-laplace、susan等(The program includes a variety of corner detection is the method, such as the harris-laplace, susan, etc.)

说明：  数学建模最优路径问题及投资例题解答，通过matalb编程解决以上问题(Mathematical model interpolation algorithm, with the mathematical modeling, use of matble programming solve interpolation fitting mathematical modeling optimal path problem and investment examples solutions, through the matalb programming solve the above problem)

使用MATLAB实现的基于多类别的KNN算法，简称为MLKNN(Using MATLAB to achieve KNN algorithm based on multi-category, referred to as MLKNN)