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Author: Guerino Mazzola
Publisher: Springer Science & Business Media
Published: 2006-10-05
Total Pages: 390
ISBN-13: 3540368744
DOWNLOAD EBOOK →Contains all the mathematics that computer scientists need to know in one place.
Author: Guerino Mazzola
Publisher: Springer
Published: 2006-09-20
Total Pages: 388
ISBN-13: 9783540368731
DOWNLOAD EBOOK →Contains all the mathematics that computer scientists need to know in one place.
Author: Clifford Stein
Publisher:
Published: 2011
Total Pages: 525
ISBN-13: 9780131377103
DOWNLOAD EBOOK →Stein/Drysdale/Bogart's Discrete Mathematics for Computer Scientists is ideal for computer science students taking the discrete math course. Written specifically for computer science students, this unique textbook directly addresses their needs by providing a foundation in discrete math while using motivating, relevant CS applications. This text takes an active-learning approach where activities are presented as exercises and the material is then fleshed out through explanations and extensions of the exercises.
Author: Eric Lehman
Publisher:
Published: 2017-03-08
Total Pages: 988
ISBN-13: 9789888407064
DOWNLOAD EBOOK →This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.
Author: Benjamin C. Pierce
Publisher: MIT Press
Published: 1991-08-07
Total Pages: 117
ISBN-13: 0262326450
DOWNLOAD EBOOK →Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Category theory is a branch of pure mathematics that is becoming an increasingly important tool in theoretical computer science, especially in programming language semantics, domain theory, and concurrency, where it is already a standard language of discourse. Assuming a minimum of mathematical preparation, Basic Category Theory for Computer Scientists provides a straightforward presentation of the basic constructions and terminology of category theory, including limits, functors, natural transformations, adjoints, and cartesian closed categories. Four case studies illustrate applications of category theory to programming language design, semantics, and the solution of recursive domain equations. A brief literature survey offers suggestions for further study in more advanced texts. Contents Tutorial • Applications • Further Reading
Author: Guerino Mazzola
Publisher: Springer Science & Business Media
Published: 2004
Total Pages: 376
ISBN-13: 9783540208358
DOWNLOAD EBOOK →This two-volume textbook is a self-contained yet comprehensive presentation of mathematics. The numerous course examples are motivated by computer science and bear a generic scientific meaning. For the second edition the entire text has been carefully re-written. Many examples and illustrations have been added, and explanations have been clarified. This makes the book more accessible to both instructors and students.
Author: V. K . Balakrishnan
Publisher: Courier Corporation
Published: 2012-04-30
Total Pages: 260
ISBN-13: 0486140385
DOWNLOAD EBOOK →This concise, undergraduate-level text focuses on combinatorics, graph theory with applications to some standard network optimization problems, and algorithms. More than 200 exercises, many with complete solutions. 1991 edition.
Author: Guerino Mazzola
Publisher: Springer
Published: 2006-03-30
Total Pages: 355
ISBN-13: 3540269371
DOWNLOAD EBOOK →This second volume of a comprehensive tour through mathematical core subjects for computer scientists completes the ?rst volume in two - gards: Part III ?rst adds topology, di?erential, and integral calculus to the t- ics of sets, graphs, algebra, formal logic, machines, and linear geometry, of volume 1. With this spectrum of fundamentals in mathematical e- cation, young professionals should be able to successfully attack more involved subjects, which may be relevant to the computational sciences. In a second regard, the end of part III and part IV add a selection of more advanced topics. In view of the overwhelming variety of mathematical approaches in the computational sciences, any selection, even the most empirical, requires a methodological justi?cation. Our primary criterion has been the search for harmonization and optimization of thematic - versity and logical coherence. This is why we have, for instance, bundled such seemingly distant subjects as recursive constructions, ordinary d- ferential equations, and fractals under the unifying perspective of c- traction theory.
Author: Harry Lewis
Publisher: Princeton University Press
Published: 2019-03-19
Total Pages: 408
ISBN-13: 0691179298
DOWNLOAD EBOOK →Discrete mathematics is the basis of much of computer science, from algorithms and automata theory to combinatorics and graph theory. Essential Discrete Mathematics for Computer Science aims to teach mathematical reasoning as well as concepts and skills by stressing the art of proof. It is fully illustrated in color, and each chapter includes a concise summary as well as a set of exercises.
Author: Michael Oberguggenberger
Publisher: Springer
Published: 2018-10-24
Total Pages: 372
ISBN-13: 3319911554
DOWNLOAD EBOOK →This easy-to-follow textbook/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling. The text describes the mathematical theory alongside the basic concepts and methods of numerical analysis, enriched by computer experiments using MATLAB, Python, Maple, and Java applets. This fully updated and expanded new edition also features an even greater number of programming exercises. Topics and features: describes the fundamental concepts in analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives, integrals, and curves; discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes added material on hyperbolic functions, curves and surfaces in space, second-order differential equations, and the pendulum equation (NEW); contains experiments, exercises, definitions, and propositions throughout the text; supplies programming examples in Python, in addition to MATLAB (NEW); provides supplementary resources at an associated website, including Java applets, code source files, and links to interactive online learning material. Addressing the core needs of computer science students and researchers, this clearly written textbook is an essential resource for undergraduate-level courses on numerical analysis, and an ideal self-study tool for professionals seeking to enhance their analysis skills.
