辛普森 COMPUETO

应用背景采用arm7芯片stm32f103zet6 编写，将单片机中的数据经过串口外设传输到电脑上，实现rs232串口运用关键技术首先编写串口发送和接收函数，在电脑上的串口调试助手上向单片机发送字符串，然后单片机将该字符串在发送回电脑，实现串口

C汇编程序，用于将sic机器代码转换为对象文件。在那里是带有GUI的项目的sic/XE版本

tsp问题的蚂蚁算法-ant colony algorithm for TSP problem

DDR3走先得详细规则及注意事项，考虑的等长走线，数据线与地址线、控制线长度关系-DDR3 take detailed rules and precautions come to consider the alignment of equal length, the data line and address lines, control lines the length of the relationship between

利用SVM分类器对图像进行分类，运行环境为opencv，并且代码包内含有关于libSVM的相关文献

关于遗传算法的一些见地。特别是关于简单遗传程序设计的实现。-on Genetic Algorithms some insight. Especially on the simple genetic procedures designed to achieve.

运筹学中牛顿法和黄金分割法一位搜索的算法C++实现，我大二时自己写的作业程序。-tacticians were Newton and the Golden Section of a search algorithm C realized, I write his sophomore year at the operating procedures.

计税程序。可以计算每周收入、最近收入、从年初到目前的所得税、扣除的联邦收入税以及帐目检查等。 This program computes weekly payroll, current earnings, year to date earnings FICA tax, federal Income Tax Withheld, and check Amount.-taxable procedures. Income can be calculated weekly, recently income from the beginning of the current income tax, the deduction of federal income taxes as well as accounts of inspection. This program computes weekly payroll, current earnings, year to date earnings FICA tax, federal Income Tax Withheld, and check Amount.

This is the project of my course in the USA: Customers arrive at a service station (with a single server) according to the Poisson process with a mean arrival rate of lambda = 0.3 (customers/min). Each customer waits in queue (if present), proceeds to receive service upon his/her turn, and departs the system when the service is completed. The service time is uniformly distributed between 2.5 and 4.5 minutes. On each day, the service station is open for two hours. Any customers in queue at the end of work hours are served before closing the service station for the day. Use simulation (do 100 simulation runs) to determine

近邻传播(Affinity Propagation,AP)聚类具有不需要设定聚类个数、快速准确的优点,但无法适应于大规模数据的应用需求.针对此问题,提出了分层近邻传播聚类算 法.首先,将待聚类数据集划分为若干适合AP算法高效执行的子集,分别推举出各个子集的聚类中心;然后对所有子集聚类中心再次执行AP聚类,推举出整个数 据集的全局聚类中心;最后根据与这些全局聚类中心的相似度对聚类样本进行划分,从而实现对大规模数据的高效聚类.在真实和模拟数据集上的实验结果均表明, 与AP聚类和自适应AP聚类相比,该方法在保证较好聚类效果的同时,极大地降低了聚类的时间消耗.