Language : English
Published : 2016-10-05
Pages : 856
Computer Networking: A Top-Down Approach 7th Global Edition
For courses in Networking/Communications. Motivate your students with a top-down, layered approach to computer networking Unique among computer networking texts, the Seventh Edition of the popular Computer Networking: A Top Down Approach builds on the author’s long tradition of teaching this complex subject through a layered approach in a “top-down manner.” The text works its way from the application layer down toward the physical layer, motivating students by exposing them to important concepts early in their study of networking. Focusing on the Internet and the fundamentally important issues of networking, this text provides an excellent foundation for students in computer science and electrical engineering, without requiring extensive knowledge of programming or mathematics. The Seventh Edition has been updated to reflect the most important and exciting recent advances in networking. MasteringComputerScience(TM) not included. Students, if MasteringComputerScience is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MasteringComputerScience should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information. MasteringComputerScience is an online homework, tutorial, and assessment program designed to work with this text to engage students and improve results. Interactive, self-paced tutorials provide individualized coaching to help students stay on track. With a wide range of activities available, students can actively learn, understand, and retain even the most difficult concepts.
Some books on algorithms are rigorous but incomplete; others cover masses of material but lack rigor. Introduction to Algorithms uniquely combines rigor and comprehensiveness. The book covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers. Each chapter is relatively self-contained and can be used as a unit of study. The algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The explanations have been kept elementary without sacrificing depth of coverage or mathematical rigor.The first edition became a widely used text in universities worldwide as well as the standard reference for professionals. The second edition featured new chapters on the role of algorithms, probabilistic analysis and randomized algorithms, and linear programming. The third edition has been revised and updated throughout. It includes two completely new chapters, on van Emde Boas trees and multithreaded algorithms, substantial additions to the chapter on recurrence (now called “Divide-and-Conquer”), and an appendix on matrices. It features improved treatment of dynamic programming and greedy algorithms and a new notion of edge-based flow in the material on flow networks. Many new exercises and problems have been added for this edition. As of the third edition, this textbook is published exclusively by the MIT Press. The hardcover edition does not include a dust jacket.
About the Author
Thomas H. Cormen is Professor of Computer Science and former Director of the Institute for Writing and Rhetoric at Dartmouth College. He is the coauthor (with Charles E. Leiserson, Ronald L. Rivest, and Clifford Stein) of the leading textbook on computer algorithms, Introduction to Algorithms (third edition, MIT Press, 2009). Charles E. Leiserson is Professor of Computer Science and Engineering at the Massachusetts Institute of Technology. Ronald L. Rivest is Andrew and Erna Viterbi Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. Clifford Stein is Professor of Industrial Engineering and Operations Research at Columbia University.
This book covers the field of machine learning, which is the study of algorithms that allow computer programs to automatically improve through experience. The book is intended to support upper level undergraduate and introductory level graduate courses in machine learning.
Using Arduino, you can join the DIY movement and build an amazing spectrum of projects – limited only by your imagination! Until now, however, most Arduino books and manuals have demanded extensive “geekitude.” Not this one: it assumes you know nothing about Arduino or electronics, guides you gently up the learning curve, walks you through several real projects, and leaves you ready to do anything you want with Arduino. This lush, 4-color guide is loaded with step-by-step photos that guide you every step of the way. Your guide, John Baichtal, founding member of legendary hackerspace Twin Cities Maker, is author of Hack This! 24 Incredible Hackerspace Projects from the DIY Movement: he’s one of the world’sleading experts in getting newcomers up-to-speed with hardware projects. Baichtal’s Arduino for Beginners starts with an easy crash course in Arduino and electronics, and teaches all you need to know about safety, tools, soldering, and more. You’ll learn how to: * Detect intrusion with lasers and IR * Set up Arduino Bluetooth connections * Create useful Arduino programs from scratch * Use sensors and water controls * Conrol DC motors, servos, and stepper motors * Create projects that keep track of time * Safely control high-voltage circuits * Harvest useful parts from junk electronics, and more Along the way, you won’t just walk through building several practical projects: you’ll learn how to construct professional enclosures, so your projects won’t just look like tangled wires and bare circuit boards – they’ll actually fit and function comfortably in your home!