shuzishiyan

This matlab file plots the MUSIC spectrum for the antenna array to show the signals DOAs

creation d un programme su labview pour déterminer les caractéristique d un PV

一个车间调度的程序，其独特之处在于可以任意输入测试矩阵进行测试。(A shop scheduling program, its unique in the input test matrix can be arbitrary test.)

这是考虑光信道色散，对输入信号的影响，结果仿真了功率谱密度(This is to consider chromatic dispersion of the optical channel, the input signal, the results of simulation of the power spectral density)

时移与坐标显示范围的不同，以及频域中f的步长不同对频域图的影响。(The times and coordinates of display range of different, and the step frequency domain f different effects on the frequency domain graph.)

此程序是对无刷直流电机的反电势进行仿真的！(This program is a brushless DC motor to simulate the EMF!)

模糊算法的实现，控制专业做设计时可以参考一下(Fuzzy algorithm, control of a professional to do the design for reference)

主要用于遗传算法的简单应用,有利于初学者应用MATLAB软件.(Mainly used for simple genetic algorithm applications, is conducive to the application of MATLAB software for beginners.)

利用matlab的图像滤波说明，有源代码，很管用的(Note the use of matlab for image filtering, active code, it is useful to)

实现了 SVM 在医学图像分类中的应用，通过医学图像的实验结果验证了该方法的有效性。 对 SVM 算法进行了深入研究，结合量子行为的粒子群算法的优点，提出了一种量子行为的粒子群算法和 SVM 结合的混合分类模型，应用于医学图像的分类中。 深入研究了 K-means 算法，结合了无监督聚类和监督分类方法的优点，提出了一种 K-means 和 SVM 结合的混合分类模型，并应用于医学图像的分类中。 利用粒子群和量子行为的粒子群算法对 K-means 算法进行了改进，并将改进的K-means 算法与 SVM 算法结合形成全自动分类模型，并且把它应用于医学图像的分类中。 (SVM in the classification of medical image applications, medical images through the experimental results verify the effectiveness of the method. SVM algorithm conducted in-depth research, combined with the quantum behavior of the advantages of particle swarm optimization, PSO and SVM combined behavior of a quantum mixed classification model, applied to medical image classification. In-depth study of the K-means algorithm combines the advantages of unsupervised clustering and supervised classification method, propose a hybrid combination of a K-means and SVM classification model, and applied to the classification of medical images. Improved particle swarm algorithm using particle swarm and quantum behavior of the K-means algorithm, and improved K-means algorithm and SVM algorithm combined with the formation of a fully automatic classification model, and apply it to medical image classification.)