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Concrete Mathematics: A Foundation for Computer Science (2nd Edition) by Oren Patashnik
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The Psychology of Computer Programming
Gerald M. Weinberg - 1971
Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering.Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more.Dorset House Publishing is proud to make this important text available to new generations of programmers -- and to encourage readers of the first edition to return to its valuable lessons.
Elements of Information Theory
Thomas M. Cover - 1991
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 referencesNow 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.
Foundations of Computer Science
Behrouz A. Forouzan - 2002
Divided into five parts computer and data, computer hardware, computer software, data organization and with an introduction to some of the more advanced topics Foundations of Computer Science gives students a bird's eye view of the subject. Each chapter includes key terms, summaries, review questions, multiple-choice questions, and exercises to enhance learning, while introducing tools such as UML, structure chart and pseudocode, which students will need in order to succeed in later courses. The text is also supported by numerous figures, examples, exercises, selected solutions and a test bank, all designed to ease and aid the learning process. Updated to cover the latest technologies and changes to course requirements, this second edition features new and updated coverage of: Artificial Intelligence, Computer Ethics and Crimes, Networking, LINUX, and Security.
Java for Dummies [With CDROM]
Barry Burd - 2006
This book makes it easy From how to install and run Java to understanding classes and objects and juggling values with arrays and collections, you will get up to speed on the new features of Java 6 in no time.Discover how toUse object-oriented programmingWork with the changes in Java 6 and JDK 6Save time by reusing codeMix Java and Javascript with the new scripting toolsTroubleshoot code problems and fix bugsAll on the bonus CD-ROMCustom build of JCreator and all the code files used in the bookBonus chapters not included in the bookTrial version of Jindent, WinOne, and NetCaptor freewareSystem Requirements: For details and complete system requirements, see the CD-ROM appendix.Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Algorithms Illuminated (Part 1): The Basics
Tim Roughgarden - 2017
Their applications range from network routing and computational genomics to public-key cryptography and database system implementation. Studying algorithms can make you a better programmer, a clearer thinker, and a master of technical interviews. Algorithms Illuminated is an accessible introduction to the subject---a transcript of what an expert algorithms tutor would say over a series of one-on-one lessons. The exposition is rigorous but emphasizes the big picture and conceptual understanding over low-level implementation and mathematical details. Part 1 of the book series covers asymptotic analysis and big-O notation, divide-and-conquer algorithms and the master method, randomized algorithms, and several famous algorithms for sorting and selection.