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加权核函数的静态杂波抑制效果以及残留噪声的高斯性和独立性检验实验结果演示程序。 另外，包括Uniform和Gabor加权核函数相结合的静态杂波抑制效果以及残留噪声的高斯性和独立性检验实验结果演示程序。()

说明：  蒙特卡罗方法可以有效地解决复杂的工程问题，而MATLAB具有强大的数值计算功能。将二者结合使用，可以得到高效的解决问题的方法。本文阐述了该方法并通过实例验证了该方法的正确性和优越性。 (Monte Carlo method can effectively solve complex engineering problems, and MATLAB has powerful function of numerical calculation. The two in combination, can be cost-effective solution to the problem. This paper describes the methods and examples of the method to verify the correctness and superiority.)

Stud. Appl. Math. 118, 153-197 (2007)关于solitons的一篇文章，figure6的编程，主要是运用牛顿迭代法进行数值模拟的。(Stud. Appl. Math. 118, 153-197 (2007) on the solitons in an article, figure6 programming, primarily using Newton' s iterative method of numerical simulation.)

说明：  基于matlab/simulink的风力发电建模系统，里面有很多实用的模型可以直接使用(based on Matlab/Simulink modeling of wind power generation system, there are many practical model can be used directly)

聚类算法聚类算法聚类算法聚类算法聚类算法聚类算法聚类算法(Generalized neural network-based intrusion cluster analysis Generalized neural network-based intrusion cluster analysisGeneralized neural network-based intrusion cluster analysisGeneralized neural network-based intrusion cluster analysis)

国外人编写的一个分数阶系统的控制工具箱，可以设计分数阶控制器，评价系统性能(Abroad were prepared by a fractional order systems control toolbox, can be designed fractional order controllers, evaluation of system performance)

matlab code for new user to design any project

说明：  利用格子Boltzmann方法模拟圆柱绕流过程，看点维数的变化，和对LBM的应用(LBM simulate the Channel flow past a cylinderical obstacle)

本程序是用于在时域中分析处理轴承故障数据的，提取了各种时域的特征参数，包括均值，有效值，峭度，裕度指标，波形指标等等 适合初学者用于轴承的故障诊断中对参数的提取。（附上轴承故障数据3类共21组 正常、内圈、外圈）(This procedure is used in the time domain analysis of bearing fault data processing to extract the characteristics of various time domain parameters, including mean, RMS, kurtosis, margin indicators, wave indicators, and so suitable for beginners for bearings Fault diagnosis of parameter extraction.)

这是一个关于SIFT算法介绍的pdf和ppt的合集，可以很好地帮助初学者了解sift算法。（中英文都有）(This is a collection of pdf and ppt about SIFT algorithm. I believe it can greatly help beginners to understand SIFT algorithm.)