和第2版相比，本版内容上*大的变化是，从以IA32和x86-64为基础转变为完全以x86-64为基础。主要更新如下： 基于x86-64，大量地重写代码，首次介绍对处理浮点数据的程序的机器级支持。 处理器体系结构修改为支持64位字和操作的设计。 引入更多的功能单元和更复杂的控制逻辑，使基于程序数据流表示的程序性能模型预测更加可靠。 扩充关于用GOT和PLT创建与位置无关代码的讨论，描述了更加强大的链接技术（比如库打桩）。 增加了对信号处理程序更细致的描述，包括异步信号安全的函数等。 采用新函数，更新了与协议无关和线程安全的网络编程。

本书采用程序员最爱用的面向对象C+ +语言来描述数据结构和算法，并把数据结构原理和算法分析技术有机地结合在一起，系统介绍了各种类型的数据结构和排序、检索的各种方法。作者非常注意对每一种数据结构不同存储方法及有关算法进行分析比较。书中还引入了一些比较高级的数据结构与先进的算法分析技术，并介绍了可计算性理论的一般知识。本版的重要改进在于引入了参数化的模板，从而提高了算法中数据类型的通用性，支持高效的代码重用。本书概念清楚、逻辑性强、内容新颖，可作为大专院校计算机软件专业与计算机应用专业学生的教材和参考书，也可供计算机工程技术人员参考。

The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

This course is offered to undergraduates and is an elementary discrete mathematics course oriented towards applications in computer science and engineering. Topics covered include: formal logic notation, induction, sets and relations, permutations and combinations, counting principles, and discrete probability.

本书是计算理论领域的经典著作，被国外多所大学选用为教材。本书以注重思路、深入引导为特色，系统地介绍计算理论的三大主要内容：自动机与语言、可计算性理论和计算复杂性理论。同时，对可计算性和计算复杂性理论中的某些高级内容作了重点讲解。全书通过启发性的问题、精彩的结果和待解决问题来引导读者挑战此领域中的高层次问题。新版的一大亮点是增加了更多习题、教辅资料和部分习题解答，更加有利于教学。 全书叙述由浅入深、详略得当，重点突出，不拘泥于技术细节。可作为计算机专业高年级本科生和研究生的教材，也可作为相关专业教师和研究人员的参考书。

For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Click on "Features" tab below for more information Resources: Visit the author's website http://aima.cs.berkeley.edu/ to access both student and instructor resources including Power Point slides, syllabus. homework and exams, and solutions text problems.

Every day, we use our computers to perform remarkable feats. A simple web search picks out a handful of relevant needles from the world's biggest haystack: the billions of pages on the World Wide Web. Uploading a photo to Facebook transmits millions of pieces of information over numerous error-prone network links, yet somehow a perfect copy of the photo arrives intact. Without even knowing it, we use public-key cryptography to transmit secret information like credit card numbers; and, we use digital signatures to verify the identity of the websites we visit. How do our computers perform these tasks with such ease? This is the first book to answer that question in language anyone can understand, revealing the extraordinary ideas that power our PCs, laptops, and smartphones. Using vivid examples, John MacCormick explains the fundamental "tricks" behind nine types of computer algorithms, including artificial intelligence (where we learn about the "nearest neighbor trick" and "twenty questions trick"), Google's famous PageRank algorithm (which uses the "random surfer trick"), data compression, error correction, and much more. These revolutionary algorithms have changed our world: this book unlocks their secrets, and lays bare the incredible ideas that our computers use every day.

本书是《ACM图灵奖--计算机发展史的缩影》一书的姊妹篇。IEEE计算机先驱奖已经颁发了20届，共有108位计算机科学技术工作者获奖，其中有22位也是图灵奖的获得者。IEEE计算机先驱奖兼顾的范围较广，并打破了东西方的界限，有一批前苏联和东欧国家的学者入围。这都有利于读者更全面地了解世界各国计算机发展的情况。在系统设计与开发，尤其是在硬件方面为计算机科学技术的发展作出卓越贡献的学者均被包括在内。本书对于我国年轻的计算机工作者及所有对计算机发展史感兴趣的读者来说都是一本难得的收藏之作。

For many applications, a randomized algorithm is either the simplest or the fastest algorithm available, and sometimes both. This book introduces the basic concepts in the design and analysis of randomized algorithms. The first part of the text presents basic tools such as probability theory and probabilistic analysis that are frequently used in algorithmic applications. Algorithmic examples are also given to illustrate the use of each tool in a concrete setting. In the second part of the book, each chapter focuses on an important area to which randomized algorithms can be applied, providing a comprehensive and representative selection of the algorithms that might be used in each of these areas. Although written primarily as a text for advanced undergraduates and graduate students, this book should also prove invaluable as a reference for professionals and researchers.

(Pearson Education) Provides a fresh approach to computer networking instruction. Contents include the Internet, protocols, network core, access networks and physical media, delay and loss in packet-switched networks, routing, multimedia networking, network management, and more. DLC: Internet (Computer network).

本书是关于形式语言、自动机理论和计算复杂性方面的经典教材，是三位理论计算大师的巅峰之作，现已更新到第3版。书中涵盖了有穷自动机、正则表达式与语言、正则语言的性质、上下文无关文法及上下文无关语言、下推自动机、上下文无关语言的，陸质、图灵机、不可判定性以及难解问题等内容。 本书已被世界许多著名大学采用为计算机理论课程的教材或教学参考书，适合用作国内高校计算机专业高年级本科生或研究生的教材，还可供从事理论计算工作的研究人员参考。

""How to Think Like a Computer Scientist"" is an introduction to programming using Python, one of the best languages for beginners. This is a Free Book -- you can download it from thinkpython.com. But if you would like to make a contribution to this project, you can do it by buying a hardcopy or paying to download the electronic version here. Thank you!

Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science. August 6, 2009 Author, Jon Kleinberg, was recently cited in the New York Times for his statistical analysis research in the Internet age.

《计算机科学概论》由两位知名的计算机科学教育家编写，全面而细致地介绍了计算机科学的各个方面。书中，计算系统的每个分层都以剖析，从住处层开始，历经硬件层、程序设计层、操作系统层、应用程序层的通信层，最后讨论了计算的限制。此外，正文中穿插了大量的人物传记、历史注释、道德问题和最新的技术发展信息，有助于你进一步了解计算机科学。每章后面都附带有大量的练习，可以帮助你即时重温并掌握这一章所述的内容。 《计算机科学概论》是计算和计算机科学引论课程的理想教材，对于想要了解计算机科学概况的非专业人员，《计算机科学概论》也是一个很好的选择。

这本久负盛名的C++经典教程，时隔八年之久，终迎来史无前例的重大升级。除令全球无数程序员从中受益，甚至为之迷醉的——C++大师Stanley B. Lippman的丰富实践经验，C++标准委员会原负责人Josée Lajoie对C++标准的深入理解，以及C++先驱Barbara E. Moo在C++教学方面的真知灼见外，更是基于全新的C++11标准进行了全面而彻底的内容更新。非常难能可贵的是，书中所有示例均全部采用C++11标准改写，这在经典升级版中极其罕见——充分体现了C++语言的重大进展极其全面实践。书中丰富的教学辅助内容、醒目的知识点提示，以及精心组织的编程示范，让这本书在C++领域的权威地位更加不可动摇。无论是初学者入门，或是中、高级程序员提升，本书均为不容置疑的首选。

《组合数学》(原书第4版)侧重于组合数学的概念和思想，包括鸽巢原理、计数技术、排列组合、Polya计数法、二项式系数、容斥原理、生成函数和递推关系以及组合结构(匹配、实验设计、图)等，深入浅出地表达了作者对该领域全面和深刻的理解，介绍了历史上源于数学游戏和娱乐的大量实例，其中对Polya计数、Burnside定理等的完美处理使得不熟悉群论的学生也能够读懂。除包含第3版中的内容外，本版又进行了更新，增加了莫比乌斯反演(作为容斥原理的推广)、格路径、Schroder数等内容。此外，各章均包含大量练习题，并在书末给出了参考答案与提示。

《现代操作系统(英文版第3版)》内容为：Tanenbaum教授作为三个操作系统的设计师或联合设计师，具有长期设计开发操作系统的经验，从而把其对理论的深入理解和具体实践融入书中，使《现代操作系统(英文版第3版)》成为操作系统领域的经典之作。在《现代操作系统(英文版第3版)》第3版中，作者深入讨论了许多主题，包括：进程，线程，存储管理，文件系统，I／O死锁，接口设计，多媒体，性能权衡。以及有关操作系统设计的最新趋势。书中不仅涵盖了现代操作系统的原理和实践，而且特别关注了Linux操作系统，WindowsVista操作系统、嵌入式操作系统、实时操作系统以及多媒体操作系统。 ·涉及Windows Vista以及最新的Linux／Unix操作系统。 ·用一整章(第12章)的篇幅对用于移动设备的Syrnbian操作系统进行案例分析。 ·涵盖更多，更新的安全方面的内容。 ·重新组织内容，尽早论述关键抽象概念。 ·给出与未来操作系统发展有关的新研究成果。 ·更新和增加了编程练习。 ·在线操作系统练习(http：／／www prenhall．com／anenbaum／details．html)采用主流windows操作系统以及开源工具。 ·包括操作系统模拟练习。 海报：

The long-anticipated revision of this #1 selling book offers the most comprehensive, state of the art introduction to the theory and practice of artificial intelligence for modern applications. Intelligent Agents. Solving Problems by Searching. Informed Search Methods. Game Playing. Agents that Reason Logically. First-order Logic. Building a Knowledge Base. Inference in First-Order Logic. Logical Reasoning Systems. Practical Planning. Planning and Acting. Uncertainty. Probabilistic Reasoning Systems. Making Simple Decisions. Making Complex Decisions. Learning from Observations. Learning with Neural Networks. Reinforcement Learning. Knowledge in Learning. Agents that Communicate. Practical Communication in English. Perception. Robotics. For computer professionals, linguists, and cognitive scientists interested in artificial intelligence.