Completely self-contained, heavily illustrated, and mathematically accessible, it has a scope of application that is not limited to the solution of specialized problems. Digital Image Fundamentals. Image Enhancement in the Spatial Domain. Image Enhancement in the Frequency Domain. Image Restoration. Color Image Processing. Wavelets and Multiresolution Processing. Image Compression. Morphological Image Processing. Image Segmentation. Representation and Description. Object Recognition.

    The book will teach you about:* Neural networks, a beautiful biologically-inspired programming paradigm which enables a computer to learn from observational data* Deep learning, a powerful set of techniques for learning in neural networksNeural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and natural language processing. This book will teach you the core concepts behind neural networks and deep learning.

    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.

    In The Master Algorithm, Pedro Domingos lifts the veil to give us a peek inside the learning machines that power Google, Amazon, and your smartphone. He assembles a blueprint for the future universal learner--the Master Algorithm--and discusses what it will mean for business, science, and society. If data-ism is today's philosophy, this book is its bible.

    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.

    Some books try to give you copy-and-paste instructions for how to deal with every single system issue that may arise, but How Linux Works actually shows you how the Linux system functions so that you can come up with your own solutions. After a guided tour of filesystems, the boot sequence, system management basics, and networking, author Brian Ward delves into open-ended topics such as development tools, custom kernels, and buying hardware, all from an administrator's point of view. With a mixture of background theory and real-world examples, this book shows both "how" to administer Linux, and "why" each particular technique works, so that you will know how to make Linux work for you.

    This book provides an applications-oriented introduction to multivariate data analysis for the non-statistician, by focusing on the fundamental concepts that affect the use of specific techniques.

    D.S. Malik is ideal for a one-semester course focused on data structures. Clearly written with the student in mind, this text focuses on Data Structures and includes advanced topics in C++ such as Linked Lists and the Standard Template Library (STL). This student-friendly text features abundant Programming Examples and extensive use of visual diagrams to reinforce difficult topics. Students will find Dr. Malik's use of complete programming code and clear display of syntax, explanation, and example easy to read and conducive to learning.

    The clarity and eloquence of the presentation make it popular with teachers and students alike. The text aims to expand the reader's view of the field and to present standard material in a novel way. All of the most important topics in the field are covered with a fresh perspective, including iterative methods for systems of equations and eigenvalue problems and the underlying principles of conditioning and stability. Presentation is in the form of 40 lectures, which each focus on one or two central ideas. The unity between topics is emphasized throughout, with no risk of getting lost in details and technicalities. The book breaks with tradition by beginning with the QR factorization - an important and fresh idea for students, and the thread that connects most of the algorithms of numerical linear algebra.

    While equipping you with the minimum of theory, GUI expert Jeff Johnson presents the reality of interface design in an entertaining, anecdotal, and instructive way. * Updated to reflect the bloopers that are common today, incorporating many comments and suggestions from first edition readers. * Takes a learn-by-example approach that teaches how to avoid common errors. * Covers bloopers in a wide range of categories: GUI controls, graphic design and layout, text messages, interaction strategies, Web site design -- including search, link, and navigation, responsiveness issues, and management decision-making. * Organized and formatted so information needed is quickly found, the new edition features call-outs for the examples and informative captions to enhance quick knowledge building. * Hundreds of illustrations: both the DOs and the DON'Ts for each topic covered, with checklists and additional bloopers on www.gui-bloopers.com.

    Concepts and techniques are presented in a clear and concise style, giving readers the opportunity to master key topics.

    This logic extends far beyond the realm of computer science and into the wide and entertaining world of puzzles. In Algorithmic Puzzles, Anany and Maria Levitin use many classic brainteasers as well as newer examples from job interviews with major corporations to show readers how to apply analytical thinking to solve puzzles requiring well-defined procedures.The book's unique collection of puzzles is supplemented with carefully developed tutorials on algorithm design strategies and analysis techniques intended to walk the reader step-by-step through the various approaches to algorithmic problem solving. Mastery of these strategies--exhaustive search, backtracking, and divide-and-conquer, among others--will aid the reader in solving not only the puzzles contained in this book, but also others encountered in interviews, puzzle collections, and throughout everyday life. Each of the 150 puzzles contains hints and solutions, along with commentary onthe puzzle's origins and solution methods. The only book of its kind, Algorithmic Puzzles houses puzzles for all skill levels. Readers with only middle school mathematics will develop their algorithmic problem-solving skills through puzzles at the elementary level, while seasoned puzzle solvers will enjoy the challenge of thinking throughmore difficult puzzles.

    Many examples are taken from real-world projects. The book focuses on high-level design as well as the gritty details of the Python syntax. The provided exercises inspire the reader to think about his or her own code, rather than providing solved problems. If you're new to Object Oriented Programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply Object Oriented Programming in Python, this is the book for you. If you are an object-oriented programmer for other languages, you too will find this book a useful introduction to Python, as it uses terminology you are already familiar with. Python 2 programmers seeking a leg up in the new world of Python 3 will also find the book beneficial, and you need not necessarily know Python 2.

    The timely provision of relevant information with minimal 'noise' is critical to modern society and this is what information retrieval (IR) is all about. It is a dynamic subject, with current changes driven by the expansion of the World Wide Web, the advent of modern and inexpensive graphical user interfaces and the development of reliable and low-cost mass storage devices. Modern Information Retrieval discusses all these changes in great detail and can be used for a first course on IR as well as graduate courses on the topic.The organization of the book, which includes a comprehensive glossary, allows the reader to either obtain a broad overview or detailed knowledge of all the key topics in modern IR. The heart of the book is the nine chapters written by Baeza-Yates and Ribeiro-Neto, two leading exponents in the field. For those wishing to delve deeper into key areas there are further state-of-the-art ch

    Aiming to tell the dark secrets of computer arithmetic, this title is suitable for library developers, compiler writers, and lovers of elegant hacks.