FVCOM

说明：  基于STM32与FDC2214手势识别处理程序(Hand gesture recognition processing program based on STM32 and FDC2214)

本程序采用两重循环来实现。内层对应学生的名词计算，外层对应所有学生的名次；以GRAED为首地址的10个字来保存学生的成绩，RANK为地址的10个字填入学生的而名次(This procedure uses the double loop to achieve. Inner layer corresponds to the term student computing, the outer layer corresponds to the ranking of all students to GRAED headed by the address words to save the 10 student achievement, RANK for the address of the 10 words fill in the ranking of students)

多线程程序 非常有用的程序 可以通过这个程序，了解多线程编程-Multi-threaded program very useful program can through this process, to understand multi-threaded programming

Taxonomy is the science of naming, describing and classifying organisms and includes all plants, animals and microorganisms of the world.

keil 源文件，包含tcpip协议栈,easyweb sever(This project is migrated from Keil MCB1700 Demo code. It can run at Keil MCB1700 board with LPC17xx. Example functionality: - Clock Settings: - XTAL = 12 MHz - PLL0 = 288 MHz - CCLK = 72 MHz Due to a bug in the LPC175x family(80 pin package) that MDIO and MDC are not functioning correctly. A bit-banging on the MDIO and MDC are included in the driver. Setting MDC_MDIO_WORKAROUND to 1 will enable the bit-banging in both MDC and MDIO. For board euipped with 80-pin LPC175x, some jumper setting is necessary for EasyWEB demo. Close "E/U" jumper(near USB Device/Host) on 2 and 3. Close "E/C" jumper(Near CAN connector) on 2 and 3. The web page shows the values of analog input(AN2). This tiny webserver needs very little resources and therefore has some restrictions: - only one active TCP session at any one time - no support for fragmented IP datagrams - no buffer for TCP datagrams received in )

交直流电力系统动态分析，徐政，对柔性直流输电研究有帮助(Dynamic behavior analysis of AC/DC power system，xuzheng，can be used to study VSC-HVDC)

编写的简单的LZ78编码，mfc程序，有界面，功能较简单(Write a simple LZ78 code, MFC program, interface, function is relatively simple)

点击button按钮，从后台开启指定exe程序。(Click the button button to open the specified exe program from the background.)

说明：  IVI学习的案例，实际讲述了IVI驱动的使用方法，对于初学者很有用！(IVI case study, describes the actual use of IVI drivers, very useful for beginners!)

Python密度聚类 最近在Science上的一篇基于密度的聚类算法《Clustering by fast search and find of density peaks》引起了大家的关注(在我的博文“论文中的机器学习算法——基于密度峰值的聚类算法”中也进行了中文的描述)。于是我就想了解下基于密度的聚类算法，熟悉下基于密度的聚类算法与基于距离的聚类算法，如K-Means算法之间的区别。 基于密度的聚类算法主要的目标是寻找被低密度区域分离的高密度区域。与基于距离的聚类算法不同的是，基于距离的聚类算法的聚类结果是球状的簇，而基于密度的聚类算法可以发现任意形状的聚类，这对于带有噪音点的数据起着重要的作用。(The main goal of the density based clustering algorithm is to find high density regions separated by low density regions. Different from distance based clustering algorithm, the clustering results based on distance clustering algorithm are spherical clusters, and density based clustering algorithm can detect clustering of arbitrary shapes, which plays an important role in data with noisy points.)