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一套完整的人力资源管理系统，包括数据库的增删改查,数据库为SQL，封装了所有访问SQL的函数，程序可靠性高， 稍加修改便可使用，可供个人开发和学习使用  一套完整的人力资源管理系统，包括数据库的增删改查,数据库为SQL，封装了所有访问SQL的函数，程序可靠性高， 稍加修改便可使用，可供个人开发和学习使用   

定义并实现带头结点的循环双向链表类，除构造和析构函数外，成员函数还有取数据元素个数、插入、删除、取数据元素-definition and take the lead in achieving the cycle node type two-way linked list, in addition to the structural and destructor function, members also function from the number of data elements, insert, delete, extract the data elements

数据结构的电子教案，对各章的重点说的比较清楚-Data structure of electronic lesson plans, the focus of the chapter, said the relatively clear

每一个参加排列的数据对应二叉树的一个结点，且任一结点如果有左（右）子树，则左（右）子树各结点的数据必须小（大）于该结点的数据。中序遍历排序二叉树即得排序结果。-Order to participate in each of the data corresponding to a binary tree node, and any one node if there is left (right) subtree, then the left (right) subtree of the data node must be small (large) in the node data. Order traversal of binary tree that is the result of a sort.

分支限界tsp算法中求下界函数的值。有中文注释。-Tsp branch and bound algorithm for the lower bound of the value function. Chinese Notes.

主要是数理方程基本框架很有用,对数据结构也有帮助-main mathematical equation is the basic framework is used for the data structure also helped

神经网络中的K均值聚类算法II： 1.KMIn为输入数据文本，其中，第一个参数为所要聚类点个数，第二个参数为聚类点的维数,第三个参数为所要求聚类的个数 2.KM2OUT为经过K均值聚类算法II计算后得到的结果-Neural network in K-means clustering algorithm II: 1.KMIn input data for the text, of which the first parameter to be the number of clustering points, the second parameter is the dimension of clustering points, the third parameter for the clustering the number of requests for 2.KM2OUT after K-means clustering algorithm II calculation results

这是几个对ldap操作的jndi,可以直接编译运行，稍加更改既可用于个人ldap数据服务与服务器tomcat的连接-It is the right of the vendor ldap operation, the compiler can run, a little change can be used personal ldap data services and server connectivity tomcat

严蔚敏的数据结构各章接的主要算法c语言的代码实现,都能上机通过-the data structure of the next major chapter algorithm c language code to achieve, will be able to pass

数据结构，牛顿插值法。通过牛顿插值法求解方程-Data structure, Newton interpolation. Solving equations using the Newton interpolation