2.9 段寄存器 我们前面讲到. 8086CPU 在访问内存时要由相关部件提供内存单元的段地址和偏移地 址,送入地址加法器合成物理地址。 这里,我们要看一下,是什么部件提供段地址。 段地 址在 8086CPU 的段寄存器中存放。 8086CPU 有 4 个段寄存器: CS , DS , SS 、 ES。当 8086CPU 要访问内存时由这 4 个段寄存器提供内存单元的段地址。 我们本课中只介绍 CS o 2.10 CS 和 IP CS 和 IP 是 8086CPU 中两个最关键的寄存器,它们指示了 CPU 当前要读取指令的地
2022-09-02 17:42:04 29.23MB 王爽
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面向对象的程序设计 在Coursera上完成Java专业化的面向对象编程的工作
2022-09-01 22:31:40 21.81MB Java
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网上其他地方基本找不到的资源——Jim Adams的《Programming Role Playing Games with DirectX》第二版的源代码,用DirectX 9.0b写成的。
2022-08-31 22:03:12 29.49MB RPG 游戏编程 角色扮演 DirectX
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经典的DX11龙书,作者依然是Frank Luna,非常值得一看
2022-08-30 16:41:57 23.83MB DirectX 11 DirectX DX11
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About This Book, Use Python and QGIS to create and transform data, produce appealing GIS visualizations, and build complex map layoutsLearn undocumented features of the new QGIS processing moduleA set of user-friendly recipes that can automate the entire geospatial workflows by connecting Python GIS building blocks into comprehensive processes, Who This Book Is For, If you are a geospatial analyst who wants to learn more about automating everyday GIS tasks or a programmer who is responsible for building GIS applications,this book is for you. The short, reusable recipes make concepts easy to understand. You can build larger applications that are easy to maintain when they are put together., What You Will Learn, Build a library of reusable scripts with ScriptRunner Create, import, and edit geospatial data on disk or in memory Get to know more about dynamic mapping Create and add features to static maps Create a mapbook Reproject a vector layer Geolocate photos on a map Combine multiple rasters into one image, In Detail, QGIS Python Programming will teach you how to write Python code that works with spatial data to automate geoprocessing tasks in QGIS. It will cover topics such as querying and editing vector data and using raster data. You will also learn to create, edit, and optimize a vector layer for faster queries, reproject a vector layer, reduce the number of vertices in a vector layer without losing critical data, and convert a raster to a vector. Following this, you will come across recipes that will help you to compose static maps, create heavily customized maps, and add specialized labels and annotations. Apart from this, the book will also share a few tips and tricks based on different aspects of QGIS.
2022-08-30 14:39:24 20.47MB QGIS,Python
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Intel (R) Flash Programming Tool(FPT 15)Version: 15.0.1.1347,可用于软刷和备份主板BIOS,有32位和64位版本。
2022-08-30 04:45:30 681KB FPT15 BIOS 备份工具 软刷
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RxSwift: Reactive Programming with Swift v2.0 配套源码,看源码学的更快更透彻
2022-08-25 21:51:50 25.93MB rxswift swift
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你必须知道的495个C语言问题 (C Programming FAQs) 本书以问答的形式组织内容,讨论了学习或使用C语言的过程中经常遇到的一些问题。书中列出了C用户经常问的400多个经典问题,涵盖了初始化、数组、指针、字符串、内存分配、库函数、C预处理器等各个方面的主题,并分别给出了解答,而且结合代码示例阐明要点。 本书结构清晰,讲解透彻,是各高校相关专业C语言课程很好的教学参考书,也是各层次C程序员的优秀实践指南。 下载地址:你必须知道的495个C语言问题 全球C语言程序员集体智慧的结晶   Amazon全五星图书   权威解答495个最常遇到的C语言问题   C是一门简洁精妙的语言,掌握基本语法容易,真正能够自如运用,就不那么简单了。你难免会遇到各种各样的问题,有些可能让你百思不得其解,甚至翻遍图书馆,也找不到问题的答案。   《你必须知道的495个C语言问题》的出版填补了这一空白。书中内容是世界各地的C语言用户多年来在新闻组comp.1ang.c中讨论的成果。作者在网络版CFAQ列表的基础上进行了大幅度的扩充和丰富,结合代码示例,权威而且详细深入地解答了实际学习和工作中最常遇到的495个C语言问题,涵盖了初始化、数组、指针、字符串、内存分配、库函数、C预处理器等各个方面的主题。许多知识点的阐述都是其他资料中所没有的,弥足珍贵。   涵盖C99标准   “本书是Summit以及C FAQ在线列表的许多参与者多年心血的结晶,是C语言界最为珍贵的财富之一。我向所有C语言程序员推荐本书。”.       ——Francis Glassborow,著名C/C++专家,ACCU(C/C++用户协会)前主席   “本书清晰地阐明了Kernighan与Ritchie的The C Programming Language一书中许多简略的地方,而且精彩地总结了C语言编程实践,强烈推荐!”       ——Yechiel M.Kimchi,以色列理工学院
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C Programming Language, 2nd Edition 英文版 第2版 PDF 扫描版 Dennis Ritchie
2022-08-21 21:17:01 20.27MB C Programming Language Dennis
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This guide is ideal if you're a professional, manager, or student who wants practical knowledge of analyzing data, without having to get a PhD in statistics. It's also good for people who have a PhD in statistics, but may not know how to write programs that apply statistical methods to real data. Discover how to apply the R language to data analysis through active learning and hands-on demonstration. You'll learn how to use R libraries that useful and reliable for data analysis, and how they can save you time and stress. Learn from a PhD-level statistician who develops and leads R courses Start analyzing data with R, rather than absorb academic statistics concepts Run more powerful analyses and make better-looking graphs Spend less time coding, with ggplot2, plyr, reshape2, and lubridate Learn how to make decisions during a data analysis
2022-08-20 12:50:20 7.41MB Hands-On Programming With R
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