自己做的 只是拿去验证一些定理以及示波器的使用 学会那个软件哦

I developed this textbook while teaching the course Statistics for Financial Engineering to master’s students in the financial engineering program at Cornell University. These students have already taken courses in portfolio management, fixed income securities, options, and stochastic calculus, so I concentrate on teaching statistics, data analysis, and the use of R, and I cover most sections of Chaps. 4–12 and 18–20. These chapters alone are more than enough to fill a one-semester course. I do not cover regression (Chaps. 9–11 and 21) or the more advanced time series topics in Chap. 13, since these topics are covered in other courses. In the past, I have not covered cointegration (Chap. 15), but I will in the future. The master’s students spend much of the third semester working on projects with investment banks or hedge funds. As a faculty adviser for several projects, I have seen the importance of cointegration.

This book does not teach R programming, but each chapter has an “R lab” with data analysis and simulations. Students can learn R from these labs and by using R’s help or the manual An Introduction to R (available at the CRAN web site and R’s online help) to learn more about the functions used in the labs. Also, the text does indicate which R functions are used in the examples. Occasionally, R code is given to illustrate some process, for example, in Chap. 16 finding the tangency portfolio by quadratic programming. For readers wishing to use R, the bibliographical notes at the end of each chapter mention books that cover R programming and the book’s web site contains examples of the R and WinBUGS code used to produce this book. Students enter my course Statistics for Financial Engineering with quite disparate knowledge of R. Some are very accomplished R programmers, while others have no experience with R, although all have experience with some programming language. Students with no previous experience with R generally need assistance from the instructor to get started on the R labs. Readers using this book for self-study should learn R first before attempting the R labs.

行业制造-电动装置-一种全动态过程电力系统戴维南等值的跟踪计算方法.zip

北邮有源二端网络等效参数测量及戴维南定理的验证

这是一份很不错的文件，是一份很不错的关于MATLAB课程设计的参考资料，大家可自行修改

戴维医疗：2021年半年度报告.PDF

包含书中全部示例代码,添加了一些注释.有的较难的算法没有完全实现(没有测试完成)

#资源达人分享计划#

《数字设计和计算机体系结构》以一种流行的方式介绍了从计算机组织和设计到更细节层次的内容，涵盖了数字逻辑设计的主要内容，展示了使用VHDL和Verilog这两种主要硬件描述语言设计MIPS处理器的技术细节，并通过MIPS微处理器的设计强化数字逻辑的概念。《数字设计和计算机体系结构》的典型特色是将数字逻辑和计算机体系结构融合，教学内容反映了当前数字电路设计的主流方法，并突出计算机体系结构的工程特点，书中的大量示例及习题设计也可以加强读者对基本概念和技术的理解和记忆。 《数字设计和计算机体系结构》不仅适合作为计算机、电子工程、电气与控制等专业的教材，同时也适合从事数字电路设计的工程师和技术人员参考。