montecarlo

Bayesian estimation methods matlab program, this is a simple example

用Matlab编写的Mie theory计算程序。在光子学中运用广泛，使用非常方便。(prepared using Matlab Mie theory calculation procedures. Photonics in extensive use, the use is very convenient.)

毕业设计中，用Matlab实现了机器人最优路径规划中的全局路径规划，算法采用的是基于方向权的 YJROsM 二叉树算法，同时结合了哈夫曼编码二叉树的 RYhlAgF综合。(Graduation design, using Matlab to achieve the optimal path planning of robot global path planning algorithm uses a binary tree algorithm based on the direction of the right YJROsM , combined with the binary tree Huffman coding RYhlAgF comprehensive.)

《现代永磁同步电机控制原理及MATLAB仿真》，袁雷编著，北京航空航天大学出版社 , 2016.04 的书籍源码，可以再此基础上对其进行编程。( Modern permanent magnet synchronous motor control principle and MATLAB simulation , Yuan Lei edited, Beijing University of Aeronautics and Astronautics Press, 2016.04 Of the book source, you can then on the basis of its programming)

基于matlab/simulink的异步电机直接转矩控制，仿真运行正常。(Based on matlab/simulink asynchronous motor direct torque control, simulation run correctly.)

PSO AND PID TUNING PARAMETERS

information coding theory with help of matlab

数字信号处理专业课程设计报告书，有关实验报告及相关的matlab程序。(Digital signal processing curriculum design report about lab reports and related matlab program.)

Hybrid GA & PSO Algorithm Run the file MainHGAPSO

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.)