MTN-Lecture-1

说明：  matlab 实现的全景图像拼接，希望对大家能有所帮助(matlab implementation of the panoramic image mosaic, we want to help)

checking the area of with respect to power quality parameter

粗糙集结合遗传算法纠结是集中的一个问题，附论文和论文中的代码。(Tangled rough sets and genetic algorithm is a problem concentrated, with papers and papers code.)

matlab环境下，基于matlab的gps p码的源程序(P-code matlab-based GPS)

流体粒子仿真工具，读取FCS 2.0 或3.0格式的文件，进行流体仿真。(This Matlab GUI enables you to perform evaluation on FCS format data files measured by flow cytometry. The following features are included (version 2.2): reading FCS 2.0 and FCS 3.0 list mode (LM) file format. The user can multiselect more LM files in the "Open LM File" dialog box defining a set of LM files to be evaluate.)

bulk endpoint endless source/sink firmware. EP2OUT will always accept a bulk OUT EP4OUT will always accept a bulk OUT EP6IN will always return a 512 byte packet. The packet contains an incrementing byte starting at 0x02. Since EP6 always returns a 512 byte packet, this endpoint should never be accessed except with a high-speed host controller. EP8IN will continuously return the packet most recently written to EP4OUT

在MATLAB环境下四个实验,压缩解压以便日后使用(change picture)

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.)

(cvpr12)Automatic Mitral Leaflet Tracking源代码((cvpr12)Automatic Mitral Leaflet Tracking)

切削力建模,仿真以及优化依据Altintas machining automation(cutting force modeling)