GA

说明：  详细的介绍用Matlab处理数字信号的方法(Detailed introduction of digital signal processing using Matlab method)

说明：  一个用MATLAB的蒙特卡罗方法模拟放射性粒子运动轨迹的东西，很好玩的，大家可以一起讨论一下··(A simulation using the Monte Carlo method in the MATLAB something of the radioactive particle trajectories, it was fun, we can discuss it with)

对于多项式y(i) = b0 + b1 * x + b2 * x^2 + b3 * x^3 + ...... bn * x^n 用递推最小二乘法来估计上式中的b0, b1, ..., bn(for polynomial y (i) = b0 b1 b2* x* x* b3 ^ 2 x ^ 3 ...... bn* x ^ n recursive least squares method used to estimate the on-belts, b1, ..., bn)

这是一个SVM的故障诊断应用程序，利用MATLAB可以直接运行程序(This is a SVM for fault diagnosis application, use of MATLAB can run programs)

适合任何信号的模糊函数的画法。运行时要明白要要输入的那几个字母的实际含义。首先要将你的信号进行离散化，Signal elements（u_basic）就是你的信号矢量。Frequency coding in units of 1/tb你信号的采样频率，Over sampling ratio表示要满足采样定理（采样频率大于两边以上信号最高频率），其他的直接翻译过来就可以了 (Ambiguity function for any signal of painting. Run-time to understand that to enter a few letters to the actual meaning. First, you want to discrete signals, Signal elements (u_basic) is your signal vector. Frequency coding in units of 1/tb your signal sampling frequency, Over sampling ratio that should satisfy the sampling theorem (sampling frequency is greater than the highest frequency signal on both sides of the above), the other can be directly translated to the)

ababoost级联分类器,通过一组弱分类器形成一个强分类器(cascade of classification)

这是一篇关于相位估计DFT算法的文章。(Frequency estimated Review)

matlab实现人脸识别，图像定位，表情捕捉等(Matlab face recognition, image positioning, expression capture, etc)

基于最小二乘支持向量机理论,结合某风电场实测风速数据,建立了最小二乘支持向量机风速预测模型。对该风电场的风速进行了提前1h的预测,其预测的平均绝对百分比误差仅为8.55 ,预测效果比较理想。同时将文中的风速预测模型与神经网络理论、支持向量机(support vector machine,SVM)理论建立的风速预测模型进行了比较。仿真结果表明,文中所提模型在预测精度和运算速度上皆优于其他模型。 (Based on least squares support vector machine theory, combined with a wind farm measured wind speed data, the establishment of a wind vector machine forecasting model of least squares support. The velocity of the wind farm were predicted in advance 1h, the mean absolute percentage error of only 8.55 of its forecast, forecast effect is ideal. While the text of the wind speed forecasting models and neural networks, support vector machines (support vector machine, SVM) wind speed prediction models were compared with established theories. Simulation results show that our proposed model on prediction accuracy and computing speed are superior to other models.)

说明：  Matlab实现ASK、BPSK 简练高效的ASK、BPSK的实现代码(Matlab ASK, BPSK concise and efficient ASK, the realization code BPSK)