▍1. grnl1
本程序建立了一个基因转录调控网络，并运用了隐含因子(The program established a gene transcription regulatory networks and the use of a hidden factor)
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▍2. TALK3
服务器与客户端分开的简单聊天程序，对于初学者有很大帮助。(Separate client and server simple chat program, very helpful for beginners.)
▍3. PtoP-CHAT
点对点聊天工具，完整的工程,学习网络编程的可以参考(POINT TO POINT CHAT)
▍4. LoginQQ
VC++自动登陆QQ的代码,VS2010的编译环境(The automatic landing VC++ QQ code, VS2010 the compiler environment)
▍5. sjwl
一个人工智能的神经网络问题，VC环境下编译，很适合对人工智能感兴趣的朋友学习(An artificial intelligence neural network problem, the VC environment compiler, it is suitable to study artificial intelligence interested friends)
▍6. motion_detection
在vc2010环境中，可实现运动目标检测，效果不错，学习的好资料(Can be realized in vc2010 environment, moving target detection, good results)
▍7. UDPTest
UDP协议测试工具，可根据设定绑定UDP绑定IPD端口，进行相关的UDP吸引收发数据测试。(UDP protocol test tools, according to the set bound to the UDP binding IPD port, the UDP attract send and receive data test.)
▍8. iperf_win
Iperf windows版，新手学习用，相当不错.(Iperf windows version, novices to learn, is quite good.)
▍9. IEEE-node
上传的代码关于粒子群无功优化仿真节点为6个初始化的程序(Uploaded code reactive particle swarm optimization simulation node 6 initialization procedure)
▍10. rengongshenjingwangluo
基于matlab的神经网络分析，有一个完整的算例，很好用。(Matlab-based neural network analysis, a complete example of good use.)
▍11. MFC-ATL-SDK-Socket
MFC、ATL、SDK、SOCKET 等概念的辨析，详细解读(The Concept of MFC, ATL, SOCKET, detailed interpretation)
▍12. A-exchange-market-trading-system
构建结合GHSOM和SVR的外汇市场交易系统结合GHSOM和SVR(A foreign exchange market trading system by combining GHSOM and SVR)
▍13. Levenshtein-Distance
在日常应用中，文本比较是一个比较常见的问题。文本比较算法也是一个老生常谈的话题(In everyday applications, the text comparison, is a relatively common problem of text comparison algorithm is a cliche topic)
▍14. BP
说明： BP函数逼近,通过BP算法对函数进行逼近，最后趋于稳定。(BP function approximation by BP algorithm to approximate the function, and finally stabilized.)
▍15. lesson-14
孙鑫VC++教学课程lesson14：网络的相关知识，网络程序的编写，Socket是连接应用程序与网络驱动程序的桥梁，Socket在应用程序中创建，通过bind与驱动程序建立关系。此后，应用程序送给Socket的数据，由Socket交给驱动程序向网络上发送出去。计算机从网络上收到与该Socket绑定的IP+Port相关的数据后，由驱动程序交给Socket，应用程序便可从该Socket中提取接收到的数据。网络应用程序就是这样通过socket进行数据的发送与接收的。TCP与UDP的工作原理与编写过程，如何在程序中链接库文件。一个字符界面的聊天程序。(Sun Xin VC++ tutorial lesson14: the knowledge of the network, network program, Socket is connected applications and network drivers bridges, Socket application to create, build relationships bind driver. Thereafter, the data of the application to give socket, by the Socket handed driver and sent out on the network. After binding with the Socket IP+Port related data is received by the computer from the network, by the driver to the socket, the application can extract the data received from the Socket. Network application is sending and receiving data through the socket. TCP and UDP works and the writing process, how to link library files in the program. A character interface chat program.)
▍16. DownLoad
基于HTTP协议的支持断点续传的下载软件源码(HTTP protocol support for HTTP-based download software source)
▍17. MH2.3CODE
11mh的辅助源码，下载研究去吧！！！！(Source of the 11mh the secondary, download study go! ! ! !)
▍18. Neural-network-quxianbijin
设计并训练三种神经网络使之分别逼近下列函数，精度Sm偏差小于20，Ry偏差小于1.5。 (各变量取值范围： =20～90, =35～55,a1=3～13, a2=0.3～3,Sd=0.05～0.45, =0.05～0.04,L2=0.015～0.06,T=7～110)(Design and training of three neural networks respectively approximation of the following function, precision Sm deviation is less than 20 Ry deviation is less than 1.5. (Each variable ranges: = 20 to 90, a = 35 to 55, a1 = 3 to 13, a2 = 0.3 to 3, Sd = 0.05 ~~ 0.45 = of 0.05 ~~ 0.04 L2 = 0.015 to 0.06, T = 7 ~~ 110))
▍19. Neural-network-hanshunihe
设计并训练一神经网络使之逼近下列函数，x，y取值范围（0，3），函数精度0.02。函数为三角函数(Design and training of a neural network approximation the following functions, x, y in the range (0,3), the function accuracy 0.02. Function trigonometric functions)
▍20. Neural-network-qiduanma
设用7个短线段构成1,2,3,4,5,6,7,8,9,10共10个数码图形，令这7个线段分别用一个矢量 来代表，又设对数码图形中用到的线段，相应分量取值为1，未用到的线段相应的分量取值为0，因此每个数码图形分别可由一个矢量表示，其顺序编号为： ，试设计一神经网络，能够区分奇数码和偶数码。(Set with seven short line segments 1, 2, 3, 4, 5, 10 digital graphics, 7 segment represented by a vector, and digital graphics used in the segment, the corresponding component value of 1, and the unused segments corresponding component value of 0 can be a vector, respectively, so that each digital graphics, its sequence number is: trial design of a neural network, it is possible to distinguish the odd and even digital.)
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