On the Foundations of Computing
On the Foundations of Computing

Author: Giuseppe Primiero

Publisher:

Published: 2020

Total Pages: 317

ISBN-13: 0198835647

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"On The Foundations of Computing is a technical, historical and conceptual investigation in the three main methodological approaches to the computational sciences: mathematical, engineering and experimental. The first part of the volume explores the background behind the formal understanding of computing, originating at the end of the XIX century, and it invesitagtes the formal origins and conceptual development of the notions of computation, algorithm and program. The second part of the volume overviews the construction of physical devices to perform automated tasks and it considers associated technical and conceptual issues. We start from the design and construction of the first generation of computing machines, explore their evolution and progress in engineering (for both hardware and software), and investigate their theoretical and conceptual problems. The third part of the volume analyses the methods and principles of experimental sciences founded on computational methods. We study the use of machines to perform scientific tasks, with particular reference to computer models and simulations. Each part aims at defining a notion of computational validity according to the corresponding methodological approach"--

A Brief History of Computing
A Brief History of Computing

Author: Gerard O'Regan

Publisher: Springer Science & Business Media

Published: 2012-03-05

Total Pages: 284

ISBN-13: 144712359X

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This lively and fascinating text traces the key developments in computation – from 3000 B.C. to the present day – in an easy-to-follow and concise manner. Topics and features: ideal for self-study, offering many pedagogical features such as chapter-opening key topics, chapter introductions and summaries, exercises, and a glossary; presents detailed information on major figures in computing, such as Boole, Babbage, Shannon, Turing, Zuse and Von Neumann; reviews the history of software engineering and of programming languages, including syntax and semantics; discusses the progress of artificial intelligence, with extension to such key disciplines as philosophy, psychology, linguistics, neural networks and cybernetics; examines the impact on society of the introduction of the personal computer, the World Wide Web, and the development of mobile phone technology; follows the evolution of a number of major technology companies, including IBM, Microsoft and Apple.

Mathematical Foundations for Computing
Mathematical Foundations for Computing

Author: G. P. McKeown

Publisher: Palgrave

Published: 1995

Total Pages: 424

ISBN-13:

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This text gives a description of the fundamental mathematical concepts used by computer scientists, while also emphasizing the need for careful justification. It provides proofs of all the major results, and all the algorithms presented are developed carefully and their performance analyzed. Throughout, the aim is to provide a well-balanced treatment of both the discrete and continuous mathematics that should be studied by the serious student of computer science. The book should therefore be most suited to those undergraduate programmes that put the emphasis on such areas as programming language semantics, program correctness, and algorithm analysis and design.

The Foundations of Computability Theory
The Foundations of Computability Theory

Author: Borut Robič

Publisher: Springer Nature

Published: 2020-11-13

Total Pages: 422

ISBN-13: 3662624214

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This book offers an original and informative view of the development of fundamental concepts of computability theory. The treatment is put into historical context, emphasizing the motivation for ideas as well as their logical and formal development. In Part I the author introduces computability theory, with chapters on the foundational crisis of mathematics in the early twentieth century, and formalism. In Part II he explains classical computability theory, with chapters on the quest for formalization, the Turing Machine, and early successes such as defining incomputable problems, c.e. (computably enumerable) sets, and developing methods for proving incomputability. In Part III he explains relative computability, with chapters on computation with external help, degrees of unsolvability, the Turing hierarchy of unsolvability, the class of degrees of unsolvability, c.e. degrees and the priority method, and the arithmetical hierarchy. Finally, in the new Part IV the author revisits the computability (Church-Turing) thesis in greater detail. He offers a systematic and detailed account of its origins, evolution, and meaning, he describes more powerful, modern versions of the thesis, and he discusses recent speculative proposals for new computing paradigms such as hypercomputing. This is a gentle introduction from the origins of computability theory up to current research, and it will be of value as a textbook and guide for advanced undergraduate and graduate students and researchers in the domains of computability theory and theoretical computer science. This new edition is completely revised, with almost one hundred pages of new material. In particular the author applied more up-to-date, more consistent terminology, and he addressed some notational redundancies and minor errors. He developed a glossary relating to computability theory, expanded the bibliographic references with new entries, and added the new part described above and other new sections.

A Companion to Digital Humanities
A Companion to Digital Humanities

Author: Susan Schreibman

Publisher: John Wiley & Sons

Published: 2008-03-03

Total Pages: 642

ISBN-13: 1405168064

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This Companion offers a thorough, concise overview of the emerging field of humanities computing. Contains 37 original articles written by leaders in the field. Addresses the central concerns shared by those interested in the subject. Major sections focus on the experience of particular disciplines in applying computational methods to research problems; the basic principles of humanities computing; specific applications and methods; and production, dissemination and archiving. Accompanied by a website featuring supplementary materials, standard readings in the field and essays to be included in future editions of the Companion.

Foundations of Computer Technology
Foundations of Computer Technology

Author: Alexander John Anderson

Publisher: CRC Press

Published: 1994-09-08

Total Pages: 456

ISBN-13: 9780412598104

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Foundations of Computer Technology is an easily accessible introduction to the architecture of computers and peripherals. This textbook clearly and completely explains modern computer systems through an approach that integrates components, systems, software, and design. It provides a succinct, systematic, and readable guide to computers, providing a springboard for students to pursue more detailed technology subjects. This volume focuses on hardware elements within a computer system and the impact of software on its architecture. It discusses practical aspects of computer organization (structure, behavior, and design) delivering the necessary fundamentals for electrical engineering and computer science students. The book not only lists a wide range of terms, but also explains the basic operations of components within a system, aided by many detailed illustrations. Material on modern technologies is combined with a historical perspective, delivering a range of articles on hardware, architecture and software, programming methodologies, and the nature of operating systems. It also includes a unified treatment on the entire computing spectrum, ranging from microcomputers to supercomputers. Each section features learning objectives and chapter outlines. Small glossary entries define technical terms and each chapter ends with an alphabetical list of key terms for reference and review. Review questions also appear at the end of each chapter and project questions inspire readers to research beyond the text. Short, annotated bibliographies direct students to additional useful reading.

Funding a Revolution
Funding a Revolution

Author: National Research Council

Publisher: National Academies Press

Published: 1999-02-11

Total Pages: 300

ISBN-13: 0309062780

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The past 50 years have witnessed a revolution in computing and related communications technologies. The contributions of industry and university researchers to this revolution are manifest; less widely recognized is the major role the federal government played in launching the computing revolution and sustaining its momentum. Funding a Revolution examines the history of computing since World War II to elucidate the federal government's role in funding computing research, supporting the education of computer scientists and engineers, and equipping university research labs. It reviews the economic rationale for government support of research, characterizes federal support for computing research, and summarizes key historical advances in which government-sponsored research played an important role. Funding a Revolution contains a series of case studies in relational databases, the Internet, theoretical computer science, artificial intelligence, and virtual reality that demonstrate the complex interactions among government, universities, and industry that have driven the field. It offers a series of lessons that identify factors contributing to the success of the nation's computing enterprise and the government's role within it.

Lessons in Enumerative Combinatorics
Lessons in Enumerative Combinatorics

Author: Ömer Eğecioğlu

Publisher: Springer Nature

Published: 2021-05-13

Total Pages: 479

ISBN-13: 3030712508

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This textbook introduces enumerative combinatorics through the framework of formal languages and bijections. By starting with elementary operations on words and languages, the authors paint an insightful, unified picture for readers entering the field. Numerous concrete examples and illustrative metaphors motivate the theory throughout, while the overall approach illuminates the important connections between discrete mathematics and theoretical computer science. Beginning with the basics of formal languages, the first chapter quickly establishes a common setting for modeling and counting classical combinatorial objects and constructing bijective proofs. From here, topics are modular and offer substantial flexibility when designing a course. Chapters on generating functions and partitions build further fundamental tools for enumeration and include applications such as a combinatorial proof of the Lagrange inversion formula. Connections to linear algebra emerge in chapters studying Cayley trees, determinantal formulas, and the combinatorics that lie behind the classical Cayley–Hamilton theorem. The remaining chapters range across the Inclusion-Exclusion Principle, graph theory and coloring, exponential structures, matching and distinct representatives, with each topic opening many doors to further study. Generous exercise sets complement all chapters, and miscellaneous sections explore additional applications. Lessons in Enumerative Combinatorics captures the authors' distinctive style and flair for introducing newcomers to combinatorics. The conversational yet rigorous presentation suits students in mathematics and computer science at the graduate, or advanced undergraduate level. Knowledge of single-variable calculus and the basics of discrete mathematics is assumed; familiarity with linear algebra will enhance the study of certain chapters.

Foundations of Data Science
Foundations of Data Science

Author: Avrim Blum

Publisher: Cambridge University Press

Published: 2020-01-23

Total Pages: 433

ISBN-13: 1108617360

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This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Foundations of Quantum Programming
Foundations of Quantum Programming

Author: Mingsheng Ying

Publisher: Elsevier

Published: 2024-04-29

Total Pages: 474

ISBN-13: 0443159432

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Quantum computers promise dramatic advantages in processing speed over currently available computer systems. Quantum computing offers great promise in a wide variety of computing and scientific research, including Quantum cryptography, machine learning, computational biology, renewable energy, computer-aided drug design, generative chemistry, and any scientific or enterprise application that requires computation speed or reach beyond the limits of current conventional computer systems. Foundations of Quantum Programming, Second Edition discusses how programming methodologies and technologies developed for current computers can be extended for quantum computers, along with new programming methodologies and technologies that can effectively exploit the unique power of quantum computing. The Second Edition includes two new chapters describing programming models and methodologies for parallel and distributed quantum computers. The author has also included two new chapters to introduce Quantum Machine Learning and its programming models – parameterized and differential quantum programming. In addition, the First Edition's preliminaries chapter has been split into three chapters, with two sections for quantum Turing machines and random access stored program machines added to give the reader a more complete picture of quantum computational models. Finally, several other new techniques are introduced in the Second Edition, including invariants of quantum programs and their generation algorithms, and abstract interpretation of quantum programs. - Demystifies the theory of quantum programming using a step-by-step approach - Includes methodologies, techniques, and tools for the development, analysis, and verification of quantum programs and quantum cryptographic protocols - Covers the interdisciplinary nature of quantum programming by providing preliminaries from quantum mechanics, mathematics, and computer science, and pointing out its potential applications to quantum engineering and physics - Presents a coherent and self-contained treatment that will be valuable for academic and industrial researchers and developers - Adds new developments such as parallel and distributed quantum programming; and introduces several new program analysis techniques such as invariants generation and abstract interpretation