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Introduction to Computer Programming and Numerical Methods, Jocelyn O. Padallan


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Автор: Jocelyn O. Padallan
Название:  Introduction to Computer Programming and Numerical Methods
ISBN: 9781774076385
Издательство: Mare Nostrum (Eurospan)
Классификация:
ISBN-10: 1774076381
Обложка/Формат: Hardcover
Страницы: 277
Вес: 0.61 кг.
Дата издания: 30.12.2020
Серия: Computing & IT
Язык: English
Размер: 229 x 152
Читательская аудитория: Professional and scholarly
Ключевые слова: Algorithms & data structures,Computer programming / software development,Information technology: general issues,Program concepts / learning to program, COMPUTERS / General
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Поставляется из: Англии
Описание: Takes the readers through various techniques that are used for programming and the numerical methods involved in them, to educate them about the fundamentals and starting point of computer programming.


Introduction to algorithms  3 ed.

Автор: Cormen, Thomas H., E
Название: Introduction to algorithms 3 ed.
ISBN: 0262033844 ISBN-13(EAN): 9780262033848
Издательство: MIT Press
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Цена: 27588.00 р.
Наличие на складе: Нет в наличии.

Описание: A new edition of the essential text and professional reference, with substantial new material on such topics as vEB trees, multithreaded algorithms, dynamic programming, and edge-base flow.

Numerical Integration of Space Fractional Partial Differential Equations: Volume 1 - Introduction to Algorithms and Computer Coding in R

Автор: Younes Salehi, William E. Schiesser
Название: Numerical Integration of Space Fractional Partial Differential Equations: Volume 1 - Introduction to Algorithms and Computer Coding in R
ISBN: 1681732076 ISBN-13(EAN): 9781681732077
Издательство: Mare Nostrum (Eurospan)
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Цена: 12335.00 р.
Наличие на складе: Нет в наличии.

Описание: Partial differential equations are one of the most used widely forms of mathematics in science and engineering. Two fractional PDEs can be considered, fractional in time, and fractional in space. These two volumes are directed to the development and use of SFPDEs, with the discussion divided into an introduction to Algorithms and Computer Coding in R and applications from classical integer PDEs.

Scintific programming: C-Language,Algorithms and Models in Science

Автор: Luciano M Barone
Название: Scintific programming: C-Language,Algorithms and Models in Science
ISBN: 9814513407 ISBN-13(EAN): 9789814513401
Издательство: World Scientific Publishing
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Цена: 36432.00 р.
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Описание: The book teaches a student to model a scientific problem and write a computer program in C language to solve that problem. To do that, the book first introduces the student to the basics of C language, dealing with all syntactical aspects, but without the pedantic content of a typical programming language manual. Then the book describes and discusses many algorithms commonly used in scientific applications (e.g. searching, graphs, statistics, equation solving, Monte Carlo methods etc.).This important book fills a gap in current available bibliography. There are many manuals for programming in C, but they never explain programming technicalities to solve a given problem. This book illustrates many relevant algorithms and shows how to translate them in a working computer program.

Introduction to Reliable and Secure Distributed Programming

Автор: Christian Cachin; Rachid Guerraoui; Lu?s Rodrigues
Название: Introduction to Reliable and Secure Distributed Programming
ISBN: 3642423272 ISBN-13(EAN): 9783642423277
Издательство: Springer
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Цена: 7965.00 р.
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Описание: Failures may range from crashes to adversarial attacks by malicious processes.Cachin, Guerraoui, and Rodrigues present an introductory description of fundamental distributed programming abstractions together with algorithms to implement them in distributed systems, where processes are subject to crashes and malicious attacks.

Methods in algorithmic analysis

Автор: Dobrushkin, Vladimir A.
Название: Methods in algorithmic analysis
ISBN: 1138118044 ISBN-13(EAN): 9781138118041
Издательство: Taylor&Francis
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Цена: 12095.00 р.
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Описание:

Explores the Impact of the Analysis of Algorithms on Many Areas within and beyond Computer Science
A flexible, interactive teaching format enhanced by a large selection of examples and exercises

Developed from the author's own graduate-level course, Methods in Algorithmic Analysis presents numerous theories, techniques, and methods used for analyzing algorithms. It exposes students to mathematical techniques and methods that are practical and relevant to theoretical aspects of computer science.

After introducing basic mathematical and combinatorial methods, the text focuses on various aspects of probability, including finite sets, random variables, distributions, Bayes' theorem, and Chebyshev inequality. It explores the role of recurrences in computer science, numerical analysis, engineering, and discrete mathematics applications. The author then describes the powerful tool of generating functions, which is demonstrated in enumeration problems, such as probabilistic algorithms, compositions and partitions of integers, and shuffling. He also discusses the symbolic method, the principle of inclusion and exclusion, and its applications. The book goes on to show how strings can be manipulated and counted, how the finite state machine and Markov chains can help solve probabilistic and combinatorial problems, how to derive asymptotic results, and how convergence and singularities play leading roles in deducing asymptotic information from generating functions. The final chapter presents the definitions and properties of the mathematical infrastructure needed to accommodate generating functions.

Accompanied by more than 1,000 examples and exercises, this comprehensive, classroom-tested text develops students' understanding of the mathematical methodology behind the analysis of algorithms. It emphasizes the important relation between continuous (classical) mathematics and discrete mathematics, which is the basis of computer science.

Neutrosophic Graph Theory and Algorithms

Автор: Florentin Smarandache, Said Broumi
Название: Neutrosophic Graph Theory and Algorithms
ISBN: 1799813134 ISBN-13(EAN): 9781799813132
Издательство: Mare Nostrum (Eurospan)
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Цена: 35897.00 р.
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Описание: Graph theory is a specific concept that has numerous applications throughout many industries. Despite the advancement of this technique, graph theory can still yield ambiguous and imprecise results. In order to cut down on these indeterminate factors, neutrosophic logic has emerged as an applicable solution that is gaining significant attention in solving many real-life decision-making problems that involve uncertainty, impreciseness, vagueness, incompleteness, inconsistency, and indeterminacy. However, empirical research on this specific graph set is lacking. Neutrosophic Graph Theory and Algorithms is a collection of innovative research on the methods and applications of neutrosophic sets and logic within various fields including systems analysis, economics, and transportation. While highlighting topics including linear programming, decision-making methods, and homomorphism, this book is ideally designed for programmers, researchers, data scientists, mathematicians, designers, educators, researchers, academicians, and students seeking current research on the various methods and applications of graph theory.

Introduction to Distributed Self-Stabilizing Algorithms

Автор: Karine Altisen, Stephane Devismes, Swan Dubois, Franck Petit
Название: Introduction to Distributed Self-Stabilizing Algorithms
ISBN: 1681735369 ISBN-13(EAN): 9781681735368
Издательство: Mare Nostrum (Eurospan)
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Цена: 10811.00 р.
Наличие на складе: Нет в наличии.

Описание: This book aims at being a comprehensive and pedagogical introduction to the concept of self-stabilization , introduced by Edsger Wybe Dijkstra in 1973. Self-stabilization characterizes the ability of a distributed algorithm to converge within finite time to a configuration from which its behavior is correct (i.e., satisfies a given specification), regardless the arbitrary initial configuration of the system. This arbitrary initial configuration may be the result of the occurrence of a finite number of transient faults. Hence, self-stabilization is actually considered as a versatile non-masking fault tolerance approach, since it recovers from the effect of any finite number of such faults in a unified manner. Another major interest of such an automatic recovery method comes from the difficulty of resetting malfunctioning devices in a large-scale (and so, geographically spread) distributed system (the Internet, Pair-to-Pair networks, and Delay Tolerant Networks are examples of such distributed systems). Furthermore, self-stabilization is usually recognized as a lightweight property to achieve fault tolerance as compared to other classical fault tolerance approaches. Indeed, the overhead, both in terms of time and space, of state-of-the-art self-stabilizing algorithms is commonly small. This makes self-stabilization very attractive for distributed systems equipped of processes with low computational and memory capabilities, such as wireless sensor networks. After more than 40 years of existence, self-stabilization is now sufficiently established as an important field of research in theoretical distributed computing to justify its teaching in advanced research-oriented graduate courses. This book is an initiation course, which consists of the formal definition of self-stabilization and its related concepts, followed by a deep review and study of classical (simple) algorithms, commonly used proof schemes and design patterns, as well as premium results issued from the self-stabilizing community. As often happens in the self-stabilizing area, in this book we focus on the proof of correctness and the analytical complexity of the studied distributed self-stabilizing algorithms. Finally, we underline that most of the algorithms studied in this book are actually dedicated to the high-level atomic-state model , which is the most commonly used computational model in the self-stabilizing area. However, in the last chapter, we present general techniques to achieve self-stabilization in the low-level message passing model, as well as example algorithms.

Interval Analysis: and Automatic Result Verification

Автор: G?nter Mayer
Название: Interval Analysis: and Automatic Result Verification
ISBN: 3110500639 ISBN-13(EAN): 9783110500639
Издательство: Walter de Gruyter
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Цена: 22305.00 р.
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Описание:

This self-contained text is a step-by-step introduction and a complete overview of interval computation and result verification, a subject whose importance has steadily increased over the past many years. The author, an expert in the field, gently presents the theory of interval analysis through many examples and exercises, and guides the reader from the basics of the theory to current research topics in the mathematics of computation.

Contents

  • Preliminaries
  • Real intervals
  • Interval vectors, interval matrices
  • Expressions, P-contraction, ε-inflation
  • Linear systems of equations
  • Nonlinear systems of equations
  • Eigenvalue problems
  • Automatic differentiation
  • Complex intervals
Programming for Computations - Matlab/Octave: A Gentle Introduction to Numerical Simulations with Matlab/Octave

Автор: Linge Svein, Langtangen Hans Petter
Название: Programming for Computations - Matlab/Octave: A Gentle Introduction to Numerical Simulations with Matlab/Octave
ISBN: 3319812890 ISBN-13(EAN): 9783319812892
Издательство: Springer
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Цена: 8418.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents computer programming as a key method for solving mathematical problems. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students.

Programming for Computations: Python: A Gentle Introduction to Numerical Simulations with Python

Автор: Linge Svein, Langtangen Hans Petter
Название: Programming for Computations: Python: A Gentle Introduction to Numerical Simulations with Python
ISBN: 3319812823 ISBN-13(EAN): 9783319812823
Издательство: Springer
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Цена: 8418.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents computer programming as a key method for solving mathematical problems. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students.


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