Introduction to Computer Data Representation

Introduction to Computer Data Representation PDF

Author: Peter Fenwick

Publisher: Bentham Science Publishers

Published: 2014-04-28

Total Pages: 268

ISBN-13: 1608058824

DOWNLOAD EBOOK →

Introduction to Computer Data Representation introduces readers to the representation of data within computers. Starting from basic principles of number representation in computers, the book covers the representation of both integer and floating point numbers, and characters or text. It comprehensively explains the main techniques of computer arithmetic and logical manipulation. The book also features chapters covering the less usual topics of basic checksums and ‘universal’ or variable length representations for integers, with additional coverage of Gray Codes, BCD codes and logarithmic representations. The description of character coding includes information on both MIME and Unicode formats. Introduction to Computer Data Representation also includes historical aspects of data representation, explaining some of the steps that developers took (and the mistakes they made) that led to the present, well-defined and accepted standards of data representation techniques. The book serves as a primer for advanced computer science graduates and a handy reference for anyone wanting to learn about numbers and data representation in computers.

Computer Organisation and Architecture

Computer Organisation and Architecture PDF

Author: B.S. Chalk

Publisher: Bloomsbury Publishing

Published: 2017-03-14

Total Pages: 296

ISBN-13: 0230000606

DOWNLOAD EBOOK →

This book describes how a computer works and explains how the various hardware components are organized and interconnected to provide a platform upon which programs can be executed. It takes a simple, step-by-step approach suitable for first year undergraduates coming to the subject for the first time. The second edition of this book has been thoroughly updated to cover new developments in the field and includes new diagrams and end-of-chapter exercises. It will also be accompanied by a lecturer and student web site which will contain solutions to exercises, further exercises, PowerPoint slides and all the source code used in the book.

Frontiers in Massive Data Analysis

Frontiers in Massive Data Analysis PDF

Author: National Research Council

Publisher: National Academies Press

Published: 2013-09-03

Total Pages: 191

ISBN-13: 0309287812

DOWNLOAD EBOOK →

Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.

Introduction to Computer Organization and Data Structures

Introduction to Computer Organization and Data Structures PDF

Author: Harold S. Stone

Publisher: McGraw-Hill Companies

Published: 1972

Total Pages: 346

ISBN-13:

DOWNLOAD EBOOK →

The purpose of this text is to introduce the student to the most primitive actions of a computer and then show how the primitive actions of a computer and then show how the primitive actions can be put together to construct most of the complex actions that computers regularly perform. This text takes the student through an introductory treatment of Turing machines, into machine and assembly languages, number representation, and elementary programming. Data structures and input/output programs are the major concerns of the central portion of the text, and the concluding chapter develops techniques for analysis of programs through examples of algorithms for searching and sorting.

SymbolicC++:An Introduction to Computer Algebra using Object-Oriented Programming

SymbolicC++:An Introduction to Computer Algebra using Object-Oriented Programming PDF

Author: Kiat Shi Tan

Publisher: Springer Science & Business Media

Published: 2000-02-02

Total Pages: 692

ISBN-13: 1852332603

DOWNLOAD EBOOK →

Symbolic C++: An Introduction to Computer Algebra Using Object-Oriented Programming provides a concise introduction to C++ and object-oriented programming, using a step-by-step construction of a new object-oriented designed computer algebra system - Symbolic C++. It shows how object-oriented programming can be used to implement a symbolic algebra system and how this can then be applied to different areas in mathematics and physics. This second revised edition:- * Explains the new powerful classes that have been added to Symbolic C++. * Includes the Standard Template Library. * Extends the Java section. * Contains useful classes in scientific computation. * Contains extended coverage of Maple, Mathematica, Reduce and MuPAD.

Data Visualization

Data Visualization PDF

Author: Alexandru C. Telea

Publisher: CRC Press

Published: 2014-09-18

Total Pages: 619

ISBN-13: 1498759793

DOWNLOAD EBOOK →

Designing a complete visualization system involves many subtle decisions. When designing a complex, real-world visualization system, such decisions involve many types of constraints, such as performance, platform (in)dependence, available programming languages and styles, user-interface toolkits, input/output data format constraints, integration wi

Learning Representation for Multi-View Data Analysis

Learning Representation for Multi-View Data Analysis PDF

Author: Zhengming Ding

Publisher: Springer

Published: 2018-12-06

Total Pages: 268

ISBN-13: 3030007340

DOWNLOAD EBOOK →

This book equips readers to handle complex multi-view data representation, centered around several major visual applications, sharing many tips and insights through a unified learning framework. This framework is able to model most existing multi-view learning and domain adaptation, enriching readers’ understanding from their similarity, and differences based on data organization and problem settings, as well as the research goal. A comprehensive review exhaustively provides the key recent research on multi-view data analysis, i.e., multi-view clustering, multi-view classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete, unbalanced and large-scale multi-view learning. Learning Representation for Multi-View Data Analysis covers a wide range of applications in the research fields of big data, human-centered computing, pattern recognition, digital marketing, web mining, and computer vision.