我们数据结构课上的一些作业 包括约瑟夫环和哈夫曼树之类的几个程序...

一个合并排序算法。是按照《算法导论》书中的讲解来写的。-A plan to merge sorting algorithm. In accordance with the

用短小的c语言编出了精湛的通讯簿，值得一看 包含了插入 删除 排序等一系列操作。-notebook

题目:稀疏矩阵是指那些多数元素为0的矩阵.利用稀疏特点进行存储和计算可以大大节省存储空间,提高计算效率.实现一个能进行稀疏矩阵基本运算的运算器.基本要求:以带行逻辑连接信息的3元组顺序表表示稀疏矩阵,实现两个矩阵相加,相减和相乘的运算.矩阵的输入形式采用3元组表示,而运算结果的矩阵则以通常的阵列形式列出.概要设计:1.以带行逻辑连接信息的3元组顺序表表示稀疏矩阵2.本程序包含2个模块:(1) 各集合定义模块(2) 主程序模块-topics : sparse matrix refers to those elements for most of the matrix 0. Using sparse features storage and computation can be greatly reduced storage space and improve computational efficiency. One can achieve for sparse matrix operations basic computing device. Basic requirements : OK logical connection with the three yuan Information Group the order said the sparse matrix table to achieve two matrices together, subtract and multiply arithmetic. Matrix entry forms using three yuan Group said, and the results of the matrix operations while the usual array listed. summary of design : 1. in line with the logic of information linking the three element group said sparse chronology matrix 2. this program contains two modules : (1) Set module (2) main program module

数据结构的java实现-data structure to achieve the java

校园导游的代码极其说明-tour of the campus code extremely Note

西门子与计算机通讯程序包括源代码 程序说明 控件 及控件使用手册 使用西门子prodave 控件 这是第一版-Siemens and computer communication procedures, including source code description of the procedures for the use of manual controls and controls the use of Siemens controls prodave This is the first edition of

清华大学出版的数据结构（C++）的配套课件-Tsinghua University published the data structure (C) matching courseware

英文版Access数据库编程-English Access Database Programming

重言式是当所有逻辑变元取遍所有值时都为真的表达式。这个程序是用来对重言式进行判别的！还可以吧！牛人别见笑！-tautology is when all logic variables take out all values are true expressions. The procedure is used to tautology runs! Also! Other cattle were laughed at!

自底向上排序：思想: 将数组的个部分,两两有序数组进行合并 算法平均时间复杂度: O(nlogn) -Bottom-up sequencing: thinking: The array of parts 22 in an orderly array merge algorithm for the average time complexity: O (nlogn)