实验二波形输入与仿真实现 一、实验目的:通过本次实验掌握波形输入法制作元件的过程,掌握实验箱中时钟和扬声器的具体使用方法以及任意模值计数器的设计方法。 二、实验要求: 1、利用波开输入法设计非门电路模块。 2、利用VHDL语言输入方法设计数据选择器(参考二选一数据选择器程序),编译、定义引脚并下载到实验箱中验证

附录GW48EDA系统使用说明 第一节GW48教学实验系统原理与使用介绍 GW48系统使用注意事项 a:闲置不用GW48EDA系统时,关闭电源,拔下电源插头! b:EDA软件安装方法可参见光盘中相应目录中的中文 README. TXT:详细使用方法可

实验五AD采样电路设计 一、实验目的:通过本次实验掌握用VHDL语言设计程序能够通过时序对ADC0809器件进行控制并进行采集、输出。 二、实验要求: 1、了解并掌握ADC0809的工作原理。 2、编写相应的程序实现对ADC0809的控制

实验三序列信号发生器与序列信号检测器的设计 一、实验目的:用VHDL语言实现序列信号发生器和检测器的设计,并对其进行仿真和硬件测试。 二、实验要求: 1、利用VHDL语言设计一个8位任意序列的序列发生器,编译定义引脚并下载到实验箱中进行验证。 2、利用VHDL语言设计一个8位任意序列的序检测器,显示检测值,编译定义引脚并下载到实验箱中进行验证

桂林电子科技大学：《可编程ASIC原理》课程教学资源（实验指导书）封面

Ch. 9 Heteroscedasticity Regression disturbances whose variance are not constant across observations are heteroscedastic. In the heteroscedastic model we assume that

Ch. 7 Violations of the ideal conditions 1 ST pecification 1.1 Selection of variables Consider a initial model. which we assume that Y=x1/1+E, It is not unusual to begin with some formulation and then contemplate adding more variable(regressors) to the model

Ch. 5 Hypothesis Testing The current framework of hypothesis testing is largely due to the work of Neyman and Pearson in the late 1920s, early 30s, complementing Fisher's work on estimation. As in estimation, we begin by postulating a statistical model but instead of seeking an estimator of 6 in e we consider the question whether

Ch. 3 Estimation 1 The Nature of statistical Inference It is argued that it is important to develop a mathematical model purporting to provide a generalized description of the data generating process. A prob bility model in the form of the parametric family of the density functions p=f(:0),0E e and its various ramifications formulated in last chapter

Ch. 24 Johansen's mle for Cointegration We have so far considered only single-equation estimation and testing for cointe- gration. While the estimation of single equation is convenient and often consis- tent, for some purpose only estimation of a system provides sufficient information This is true, for example, when we consider the estimation of multiple cointe- grating vectors, and inference about the number of such vectors. This chapter examines methods of finding the cointegrating rank and derive the asymptotic