This book emphasizes the creative aspects of algorithm design by examining steps used in the process of algorithm development. The heart of the creative process lies in an analogy between proving mathematical theorems by induction and designing combinatorial algorithms. The book contains hundreds of problems and examples. It is designed to enhance the reader's problem-solving abilities and understanding of the principles behind algorithm design. 0201120372B04062001
Author: V.V. Muniswamy
Publisher: I. K. International Pvt Ltd
Release Date: 2009-01-01
This book is designed for the way we learn and intended for one-semester course in Design and Analysis of Algorithms . This is a very useful guide for graduate and undergraduate students and teachers of computer science. This book provides a coherent and pedagogically sound framework for learning and teaching. Its breadth of coverage insures that algorithms are carefully and comprehensively discussed with figures and tracing of algorithms. Carefully developing topics with sufficient detail, this text enables students to learn about concepts on their own, offering instructors flexibility and allowing them to use the text as lecture reinforcement.Key Features:" Focuses on simple explanations of techniques that can be applied to real-world problems." Presents algorithms with self-explanatory pseudocode." Covers a broad range of algorithms in depth, yet makes their design and analysis accessible to all levels of readers." Includes chapter summary, self-test quiz and exercises at the end of each chapter. Key to quizzes and solutions to exercises are given in appendices.
Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses Java as the programming language.
Comprehensive treatment focuses on creation of efficient data structures and algorithms and selection or design of data structure best suited to specific problems. This edition uses C++ as the programming language.
Author: J.A. Storer
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
Data structures and algorithms are presented at the college level in a highly accessible format that presents material with one-page displays in a way that will appeal to both teachers and students. The thirteen chapters cover: Models of Computation, Lists, Induction and Recursion, Trees, Algorithm Design, Hashing, Heaps, Balanced Trees, Sets Over a Small Universe, Graphs, Strings, Discrete Fourier Transform, Parallel Computation. Key features: Complicated concepts are expressed clearly in a single page with minimal notation and without the "clutter" of the syntax of a particular programming language; algorithms are presented with self-explanatory "pseudo-code." * Chapters 1-4 focus on elementary concepts, the exposition unfolding at a slower pace. Sample exercises with solutions are provided. Sections that may be skipped for an introductory course are starred. Requires only some basic mathematics background and some computer programming experience. * Chapters 5-13 progress at a faster pace. The material is suitable for undergraduates or first-year graduates who need only review Chapters 1 -4. * This book may be used for a one-semester introductory course (based on Chapters 1-4 and portions of the chapters on algorithm design, hashing, and graph algorithms) and for a one-semester advanced course that starts at Chapter 5. A year-long course may be based on the entire book. * Sorting, often perceived as rather technical, is not treated as a separate chapter, but is used in many examples (including bubble sort, merge sort, tree sort, heap sort, quick sort, and several parallel algorithms). Also, lower bounds on sorting by comparisons are included with the presentation of heaps in the context of lower bounds for comparison-based structures. * Chapter 13 on parallel models of computation is something of a mini-book itself, and a good way to end a course. Although it is not clear what parallel
Many programmers would love to use Perl for projects that involve heavy lifting, but miss the many traditional algorithms that textbooks teach for other languages. Computer scientists have identified many techniques that a wide range of programs need, such as: Fuzzy pattern matching for text (identify misspellings!) Finding correlations in data Game-playing algorithms Predicting phenomena such as Web traffic Polynomial and spline fitting Using algorithms explained in this book, you too can carry out traditional programming tasks in a high-powered, efficient, easy-to-maintain manner with Perl.This book assumes a basic understanding of Perl syntax and functions, but not necessarily any background in computer science. The authors explain in a readable fashion the reasons for using various classic programming techniques, the kind of applications that use them, and -- most important -- how to code these algorithms in Perl.If you are an amateur programmer, this book will fill you in on the essential algorithms you need to solve problems like an expert. If you have already learned algorithms in other languages, you will be surprised at how much different (and often easier) it is to implement them in Perl. And yes, the book even has the obligatory fractal display program.There have been dozens of books on programming algorithms, some of them excellent, but never before has there been one that uses Perl.The authors include the editor of The Perl Journal and master librarian of CPAN; all are contributors to CPAN and have archived much of the code in this book there."This book was so exciting I lost sleep reading it." Tom Christiansen
While many think of algorithms as specific to computer science, at its core algorithmic thinking is defined by the use of analytical logic to solve problems. 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 on the 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 through more difficult puzzles.
Das Teubner-Taschenbuch der Mathematik erfüllt aktuell, umfassend und kompakt alle Erwartungen, die an ein mathematisches Nachschlagewerk gestellt werden. Es vermittelt ein lebendiges und modernes Bild der heutigen Mathematik. Als Handbuch begleitet es die Studierenden vom ersten Semester an und der Praktiker nutzt es als unentbehrliches Nachschlagewerk. Der Teil II dieses erfolgreichen Werkes behandelt die vielfältigen Anwendungen der Mathematik in Informatik, Operations Research und mathematischer Physik. Das thematische Spektrum reicht von Tensoranalysis, Maßtheorie und Funktionalanalysis über Dynamische Systeme und Variationsrechnung bis zu Mannigfaltigkeiten, Riemannscher Geometrie, Liegruppen und Topologie.
Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
Release Date: 2017-04-04
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Programming skills are indispensable in today’s world, not just for computer science students, but also for anyone in any scientific or technical discipline. Introduction to Programming in Java, Second Edition, by Robert Sedgewick and Kevin Wayne is an accessible, interdisciplinary treatment that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students and professionals to learn that programming is a natural, satisfying, and creative experience, and to become conversant with one of the world’s most widely used languages. This example-driven guide focuses on Java’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Applications from applied math, physics, chemistry, biology, and computer science Drawing on their extensive classroom experience, throughout the text the authors provide Q&As, exercises, and opportunities for creative engagement with the material. Together with the companion materials described below, this book empowers people to pursue a modern approach to teaching and learning programming. Companion web site (introcs.cs.princeton.edu/java) contains Chapter summaries Supplementary exercises, some with solutions Detailed instructions for installing a Java programming environment Program code and test data suitable for easy download Detailed creative exercises, projects, and other supplementary materials Companion studio-produced online videos (informit.com/sedgewick) are available for purchase and provide students and professionals with the opportunity to engage with the material at their own pace and give instructors the opportunity to spend their time with students helping them to succeed on assignments and exams. Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.
Author: Robert Sedgewick
Publisher: Addison-Wesley Professional
Release Date: 2015-05-27
Today, anyone in a scientific or technical discipline needs programming skills. Python is an ideal first programming language, and Introduction to Programming in Python is the best guide to learning it. Princeton University’s Robert Sedgewick, Kevin Wayne, and Robert Dondero have crafted an accessible, interdisciplinary introduction to programming in Python that emphasizes important and engaging applications, not toy problems. The authors supply the tools needed for students to learn that programming is a natural, satisfying, and creative experience. This example-driven guide focuses on Python’s most useful features and brings programming to life for every student in the sciences, engineering, and computer science. Coverage includes Basic elements of programming: variables, assignment statements, built-in data types, conditionals, loops, arrays, and I/O, including graphics and sound Functions, modules, and libraries: organizing programs into components that can be independently debugged, maintained, and reused Object-oriented programming and data abstraction: objects, modularity, encapsulation, and more Algorithms and data structures: sort/search algorithms, stacks, queues, and symbol tables Examples from applied math, physics, chemistry, biology, and computer science—all compatible with Python 2 and 3 Drawing on their extensive classroom experience, the authors provide Q&As, exercises, and opportunities for creative practice throughout. An extensive amount of supplementary information is available at introcs.cs.princeton.edu/python. With source code, I/O libraries, solutions to selected exercises, and much more, this companion website empowers people to use their own computers to teach and learn the material.
Author: Francisco Bianchi
Publisher: Elsevier Brasil
Release Date: 2014-10-28
O núcleo básico de linguagem de programação na maioria dos cursos na área de computação é composto por Algoritmos e Estrutura de dados. Este livro tratará dos tópicos abordados na disciplina de Estrutura de Dados, uma continuação do livro anterior dos autores, que trata de Algoritmos e programação de computadores. Os conceitos e técnicas de programação de Estruturas de Dados são apresentados num formato que prioriza a exposição dos conceitos e problemas de forma clara e objetiva. Cada tema é trabalhado a partir de uma situação-problema, passando pela resolução da situação, ampliação do tópico, conceituação e aplicação em diversas linguagens de programação. Ao final de cada capítulo há exercícios de fixação e indicação de material para estudos complementares.
Erhvervsjournalist Brad Stone har i årtier fulgt Amazons udvikling og fortæller nu historien om virksomheden, der i Danmark mest er kendt for at sælge bøger. Men hvad skal der til for at opbygge en succesrig onlinebaseret virksomhed, der sælger alt, og som tæller ca. 90.000 medarbejdere på verdensplan? Der skal en hidsig, overintelligent og ambitiøs stifter til! En, der skarpt kan gennemskue både it-processer og forretningsmodeller, som ikke er bange for at eksperimentere, og som har tæft for at se de store perspektiver. Jeff Bezos, manden bag Amazon, lader ingen Steve Jobs tilbage i chefnykker og overfusninger. Brad Stone fortæller om manden og virksomheden, der igennem dramatiske op- og nedture, kriser og succeser har manøvreret igennem blodrødt farvand uden nogensinde at vakle. Læs om krigen mellem Amazon og bogbranchen. Mellem Amazon og Google. Mellem Amazon og eBay. Mellem Amazon og Target ...
Author: Michael R. Berthold
Release Date: 2012-06-27
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This book provides a more practical approach by explaining the concepts of machine learning algorithms and describing the areas of application for each algorithm, using simple practical examples to demonstrate each algorithm and showing how different issues related to these algorithms are applied.