rtc实时时钟试验

逆波兰式的转换- Goes against the Poland-like transformation

资源描述#include #define maxsize 100 using namespace std; /*class base {     int length; };*/ class Seqlist                //实现顺序表类 {     private:         int size;        //当前元素个数         int length;            //当前表的总长度              public:         int *elem;            //动态存放数据         Seqlist();        //构造函数的声明         int listset();    //顺序表的创建    &nbs

99表 直接生成99表。 比较简单的程序。可以了解简单的代码-99 Table 99 Table directly generated. Relatively simple procedure. Can understand simple code

k-means 算法接受输入量 k ；然后将n个数据对象划分为 k个聚类以便使得所获得的聚类满足：同一聚类中的对象相似度较高；而不同聚类中的对象相似度较小。聚类相似度是利用各聚类中对象的均值所获得一个“中心对象”（引力中心）来进行计算的。 Matlab 源代码，以兰花数据集作为测试对象。-k-means algorithm to accept input k then n data object is divided into k-clustering in order to make available to the cluster to meet: the same objects in clustering high similarity and objects in different clustering the similarity smaller. Cluster similarity is the use of the clustering of objects by means of a

检测FFT性能的MATLAB程序,系统性能检测用-MATLAB code for FFT

人工股市（Artificial Stock Market，简称ASM）是模拟股市运作的一个程序-artificial stock market (Artificial Stock Market, or ASM) is a simulation of the operation of a stock market procedures

这是C语言的 DES 加密算法在 。欢迎下载，试用。非常感谢大家的支持!

图像阈值分割---迭代算法 1.处理流程：        1.为全局阈值选择一个初始估计值T(图像的平均灰度)。        2.用T分割图像。产生两组像素：G1有灰度值大于T的像素组成，G2有小于等于T像素组成。        3.计算G1和G2像素的平均灰度值m1和m2；        4.计算一个新的阈值:T = (m1 + m2) / 2;        5.重复步骤2和4,直到连续迭代中的T值间的差小于一个预定义参数为止。     &

应用背景On the Design of ZF and MMSE Tomlinson-Harashima Precoding in Multiuser MIMO Amplify-and-Forward Relay System,it is main described the mimo system in the multi-user  scenario.the main precoding algrithm is combined the zf precoding and the MMSE precoding.关键技术we design a zero-forcing (ZF) Tomlinson-Harashima precoding (THP) and a minimum mean square error (MMSE) THP for multiuser MIMO relay system with direct link. Based on these precoding structures, we propose the optimal combining weights of the ZF THP and the MMSE THP in half duplex relay system, and the sub-optimal weights of MMSE THP to reduce feedback channel state information(CSI). Through the Monte Carlo simulation, we verify that the optimal weights combining method outperforms the constant weights combining method. In addition, we confirm that the performance of the sub-optimal weights combining method is&

loki 程序库-loki library