LLCsaber仿真文件

电动车用永磁同步电动机FOC控制系统实现_黄智宇(Realization of FOC Control System of Permanent Magnet Synchronous Motor for Electric Vehicle)

说明：  计算极大似然值copula，matlab代码(Calculate the maximum likelihood value)

The document is a introduction o ls-svm1.5. It is easy to learn and very useful!

美国GE公司MIL-1553B系列产品WINDOWS驱动程序和API函数源代码。-American GE company MIL-1553B Series Product WINDOWS drivers and API function source code.

功能说明： 1.支持UBB 2.支持版主回复. 3.支持留言删除. 4.支持管理密码修改. 5.管理员可查看留言网友IP地址. 6.过滤""字符带来的安全隐患. 后台登陆:mofei_login.asp 用户名和密码为mofei -Function Description: 1. Support UBB2. Support Moderators Reply .3. Support message delete .4. To support the management of the password modify .5. Administrators can view the message User IP Address .6.

药品管理系统，MFC+Access,MFC+SQL Server(Drug management system, MFC+Access, MFC+SQL Server)

遗传粒子群算法的程序代码，希望能帮助到你！(Genetic particle swarm optimization algorithm code, I hope to help you!)

C#与S7-1200通讯，控制AGV,前进，后退，读取AGV当前状态，写入控制，电机转速，导航偏差，RFID数据，扫描仪信息，AGV位置。(C# communicates with S7-1200, controls AGV, moves forward and backwards, reads current status of AGV, writes control, motor speed, navigation deviation, RFID data, scanner information, AGV position.)

这是一张ascii表，学计算机的人都知道它的作用，这里我就不多说了。-This is a ascii table, a computer who know their role, I am not here to talk a lot.

聚类分析是数据挖掘中重要的研究内容之一，对聚类准则进行了总结，对五类传统的聚类算法的研究 现状和进展进行了较为全面的总结，就一些新的聚类算法进行了梳理，根据样本归属关系、样本数据预处理、 样本的相似性度量、样本的更新策略、样本的高维性和与其他学科的融合等六个方面对聚类中近 20多个新算 法，如粒度聚类、不确定聚类、量子聚类、核聚类、谱聚类、聚类集成、概念聚类、球壳聚类、仿射聚类、数据流聚 类等，分别进行了详细的概括。(Clustering analysis is one of the important research contents in data mining. The clustering criteria are summarized. The research status and progress of five traditional clustering algorithms are summarized comprehensively. Some new clustering algorithms are used. By combing, according to the sample attribution relationship, sample data preprocessing, sample similarity measure, sample update strategy, sample high-dimensionality and fusion with other disciplines, nearly 20 new algorithms in clustering, Such as granular clustering, uncertain clustering, quantum clustering, nuclear clustering, spectral clustering, clustering integration, concept clustering, spherical shell clustering, affine clustering, data stream clustering, etc., respectively Generalization.)