Introduction to the Design and Analysis of Algorithms

Author: Anany Levitin

Publisher: Pearson Education

ISBN: 9780273764113

Category: Juvenile Nonfiction

Page: 589

View: 8879

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, 'Introduction to the Design and Analysis of Algorithms' presents the subject in a coherent and innovative manner.

Introduction to the Design & Analysis of Algorithms

Author: Anany Levitin

Publisher: Addison-Wesley Longman

ISBN: 9780132316811

Category: Computers

Page: 565

View: 717

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal treatment while thoroughly covering the material required in an introductory algorithms course. Popular puzzles are used to motivate students' interest and strengthen their skills in algorithmic problem solving. Other learning-enhancement features include chapter summaries, hints to the exercises, and a detailed solution manual.

Introduction to the Design & Analysis of Algorithms

Author: Anany Levitin

Publisher: Pearson Addison/Wesley

ISBN: 9780321364135

Category: Algorithmes

Page: 562

View: 8196

Based on a Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal treatment while thoroughly covering the material required in an introductory algorithms course. Popular puzzles are used to motivate students' interest and strengthen their skills in algorithmic problem solving. Other learning-enhancement features include chapter summaries, hints to the exercises, and a detailed solution manual.

Introduction to Algorithms

Author: Thomas H. Cormen

Publisher: MIT Press

ISBN: 0262033844

Category: Computers

Page: 1292

View: 465

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-based flow.

The Design and Analysis of Algorithms

Author: Dexter C. Kozen

Publisher: Springer Science & Business Media

ISBN: 1461244005

Category: Computers

Page: 322

View: 6294

These are my lecture notes from CS681: Design and Analysis of Algo rithms, a one-semester graduate course I taught at Cornell for three consec utive fall semesters from '88 to '90. The course serves a dual purpose: to cover core material in algorithms for graduate students in computer science preparing for their PhD qualifying exams, and to introduce theory students to some advanced topics in the design and analysis of algorithms. The material is thus a mixture of core and advanced topics. At first I meant these notes to supplement and not supplant a textbook, but over the three years they gradually took on a life of their own. In addition to the notes, I depended heavily on the texts • A. V. Aho, J. E. Hopcroft, and J. D. Ullman, The Design and Analysis of Computer Algorithms. Addison-Wesley, 1975. • M. R. Garey and D. S. Johnson, Computers and Intractibility: A Guide to the Theory of NP-Completeness. w. H. Freeman, 1979. • R. E. Tarjan, Data Structures and Network Algorithms. SIAM Regional Conference Series in Applied Mathematics 44, 1983. and still recommend them as excellent references.

Introduction to the Design and Analysis of Algorithms

International Edition

Author: Anany Levitin

Publisher: Pearson Higher Ed

ISBN: 1292014113

Category: Computers

Page: 592

View: 6708

Based on a new classification of algorithm design techniques and a clear delineation of analysis methods, Introduction to the Design and Analysis of Algorithms presents the subject in a coherent and innovative manner. Written in a student-friendly style, the book emphasizes the understanding of ideas over excessively formal treatment while thoroughly covering the material required in an introductory algorithms course. Popular puzzles are used to motivate students' interest and strengthen their skills in algorithmic problem solving. Other learning-enhancement features include chapter summaries, hints to the exercises, and a detailed solution manual.

DESIGN AND ANALYSIS OF ALGORITHMS

Author: PRABHAKAR GUPTA,VINEET AGARWAL,MANISH VARSHNEY

Publisher: PHI Learning Pvt. Ltd.

ISBN: 8120346637

Category: Computers

Page: 424

View: 4085

This well organized text provides the design techniques of algorithms in a simple and straight forward manner. It describes the complete development of various algorithms along with their pseudo-codes in order to have an understanding of their applications. The book begins with a description of the fundamental concepts and basic design techniques of algorithms. Gradually, it introduces more complex and advanced topics such as dynamic programming, backtracking and various algorithms related to graph data structure. Finally, the text elaborates on NP-hard, matrix operations and sorting network. Primarily designed as a text for undergraduate students of Computer Science and Engineering and Information Technology (B.Tech., Computer Science, B.Tech. IT) and postgraduate students of Computer Applications (MCA), the book would also be quite useful to postgraduate students of Computer Science and IT (M.Sc., Computer Science; M.Sc., IT). New to this Second Edition 1. A new section on Characteristics of Algorithms (Section 1.3) has been added 2. Five new sections on Insertion Sort (Section 2.2), Bubble Sort (Section 2.3), Selection Sort (Section 2.4), Shell Sort/Diminishing Increment Sort/Comb Sort (Section 2.5) and Merge Sort (Section 2.6) have been included 3. A new chapter on Divide and Conquer (Chapter 5) has also been incorporated

Algorithmic Puzzles

Author: Anany Levitin,Maria Levitin

Publisher: OUP USA

ISBN: 0199740445

Category: Computers

Page: 257

View: 8782

Algorithmic puzzles are puzzles involving well-defined procedures for solving problems. This book will provide an enjoyable and accessible introduction to algorithmic puzzles that will develop the reader's algorithmic thinking. The first part of this book is a tutorial on algorithm design strategies and analysis techniques. Algorithm design strategies — exhaustive search, backtracking, divide-and-conquer and a few others — are general approaches to designing step-by-step instructions for solving problems. Analysis techniques are methods for investigating such procedures to answer questions about the ultimate result of the procedure or how many steps are executed before the procedure stops. The discussion is an elementary level, with puzzle examples, and requires neither programming nor mathematics beyond a secondary school level. Thus, the tutorial provides a gentle and entertaining introduction to main ideas in high-level algorithmic problem solving. The second and main part of the book contains 150 puzzles, from centuries-old classics to newcomers often asked during job interviews at computing, engineering, and financial companies. The puzzles are divided into three groups by their difficulty levels. The first fifty puzzles in the Easier Puzzles section require only middle school mathematics. The sixty puzzle of average difficulty and forty harder puzzles require just high school mathematics plus a few topics such as binary numbers and simple recurrences, which are reviewed in the tutorial. All the puzzles are provided with hints, detailed solutions, and brief comments. The comments deal with the puzzle origins and design or analysis techniques used in the solution. The book should be of interest to puzzle lovers, students and teachers of algorithm courses, and persons expecting to be given puzzles during job interviews.

An Introduction to the Analysis of Algorithms

Author: Robert Sedgewick,Philippe Flajolet

Publisher: Addison-Wesley

ISBN: 0133373487

Category: Computers

Page: 604

View: 1997

Despite growing interest, basic information on methods and models for mathematically analyzing algorithms has rarely been directly accessible to practitioners, researchers, or students. An Introduction to the Analysis of Algorithms, Second Edition, organizes and presents that knowledge, fully introducing primary techniques and results in the field. Robert Sedgewick and the late Philippe Flajolet have drawn from both classical mathematics and computer science, integrating discrete mathematics, elementary real analysis, combinatorics, algorithms, and data structures. They emphasize the mathematics needed to support scientific studies that can serve as the basis for predicting algorithm performance and for comparing different algorithms on the basis of performance. Techniques covered in the first half of the book include recurrences, generating functions, asymptotics, and analytic combinatorics. Structures studied in the second half of the book include permutations, trees, strings, tries, and mappings. Numerous examples are included throughout to illustrate applications to the analysis of algorithms that are playing a critical role in the evolution of our modern computational infrastructure. Improvements and additions in this new edition include Upgraded figures and code An all-new chapter introducing analytic combinatorics Simplified derivations via analytic combinatorics throughout The book’s thorough, self-contained coverage will help readers appreciate the field’s challenges, prepare them for advanced results—covered in their monograph Analytic Combinatorics and in Donald Knuth’s The Art of Computer Programming books—and provide the background they need to keep abreast of new research. "[Sedgewick and Flajolet] are not only worldwide leaders of the field, they also are masters of exposition. I am sure that every serious computer scientist will find this book rewarding in many ways." —From the Foreword by Donald E. Knuth

Algorithms

Design Techniques and Analysis

Author: M. H. Alsuwaiyel

Publisher: World Scientific

ISBN: 9814723657

Category: Mathematics

Page: 552

View: 9349

An Introduction to the Analysis of Algorithms

Author: Michael Soltys

Publisher: World Scientific

ISBN: 981440117X

Category: Computers

Page: 212

View: 2370

A successor to the first edition, this updated and revised book is a great companion guide for students and engineers alike, specifically software engineers who design reliable code. While succinct, this edition is mathematically rigorous, covering the foundations of both computer scientists and mathematicians with interest in algorithms. Besides covering the traditional algorithms of Computer Science such as Greedy, Dynamic Programming and Divide & Conquer, this edition goes further by exploring two classes of algorithms that are often overlooked: Randomised and Online algorithms — with emphasis placed on the algorithm itself. The coverage of both fields are timely as the ubiquity of Randomised algorithms are expressed through the emergence of cryptography while Online algorithms are essential in numerous fields as diverse as operating systems and stock market predictions. While being relatively short to ensure the essentiality of content, a strong focus has been placed on self-containment, introducing the idea of pre/post-conditions and loop invariants to readers of all backgrounds. Containing programming exercises in Python, solutions will also be placed on the book's website. Contents:PreliminariesGreedy AlgorithmsDivide and ConquerDynamic ProgrammingOnline AlgorithmsRandomized AlgorithmsAppendix A: Number Theory and Group TheoryAppendix B: RelationsAppendix C: Logic Readership: Students of undergraduate courses in algorithms and programming. Keywords:Algorithms;Greedy;Dynamic Programming;Online;Randomized;Loop InvariantKey Features:The book is concise, and of a portable size that can be conveniently carried around by studentsIt emphasizes correctness of algorithms: how to prove them correct, which is of great importance to software engineersIt contains a chapter on randomized algorithms and applications to cryptography, as well as a chapter on online algorithms and applications to caching/paging, both of which are relevant and current topicsReviews: “Summing up, the book contains very nice introductory material for beginners in the area of correct algorithm's design.” Zentralblatt MATH

The Algorithm Design Manual

Author: Steven S Skiena

Publisher: Springer Science & Business Media

ISBN: 1848000707

Category: Computers

Page: 730

View: 9859

This newly expanded and updated second edition of the best-selling classic continues to take the "mystery" out of designing algorithms, and analyzing their efficacy and efficiency. Expanding on the first edition, the book now serves as the primary textbook of choice for algorithm design courses while maintaining its status as the premier practical reference guide to algorithms for programmers, researchers, and students. The reader-friendly Algorithm Design Manual provides straightforward access to combinatorial algorithms technology, stressing design over analysis. The first part, Techniques, provides accessible instruction on methods for designing and analyzing computer algorithms. The second part, Resources, is intended for browsing and reference, and comprises the catalog of algorithmic resources, implementations and an extensive bibliography. NEW to the second edition: • Doubles the tutorial material and exercises over the first edition • Provides full online support for lecturers, and a completely updated and improved website component with lecture slides, audio and video • Contains a unique catalog identifying the 75 algorithmic problems that arise most often in practice, leading the reader down the right path to solve them • Includes several NEW "war stories" relating experiences from real-world applications • Provides up-to-date links leading to the very best algorithm implementations available in C, C++, and Java

Introduction to Optimum Design

Author: Jasbir Arora

Publisher: Academic Press

ISBN: 0128009187

Category: Technology & Engineering

Page: 968

View: 4974

Introduction to Optimum Design, Fourth Edition, carries on the tradition of the most widely used textbook in engineering optimization and optimum design courses. It is intended for use in a first course on engineering design and optimization at the undergraduate or graduate level in engineering departments of all disciplines, with a primary focus on mechanical, aerospace, and civil engineering courses. Through a basic and organized approach, the text describes engineering design optimization in a rigorous, yet simplified manner, illustrates various concepts and procedures with simple examples, and demonstrates their applicability to engineering design problems. Formulation of a design problem as an optimization problem is emphasized and illustrated throughout the text using Excel and MATLAB as learning and teaching aids. This fourth edition has been reorganized, rewritten in parts, and enhanced with new material, making the book even more appealing to instructors regardless of course level. Includes basic concepts of optimality conditions and numerical methods that are described with simple and practical examples, making the material highly teachable and learnable Presents applications of optimization methods for structural, mechanical, aerospace, and industrial engineering problems Provides practical design examples that introduce students to the use of optimization methods early in the book Contains chapter on several advanced optimum design topics that serve the needs of instructors who teach more advanced courses

Computational Geometry

Algorithms and Applications

Author: Mark de Berg

Publisher: Springer Science & Business Media

ISBN: 3540779736

Category: Computers

Page: 386

View: 6608

This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.

Algorithm Design: Pearson New International Edition

Author: Jon Kleinberg,Eva Tardos

Publisher: Pearson Higher Ed

ISBN: 1292037040

Category: Computers

Page: 832

View: 9345

August 6, 2009 Author, Jon Kleinberg, was recently cited in the New York Times for his statistical analysis research in the Internet age. Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science.

Algorithms

Design and Analysis

Author: Harsh Bhasin

Publisher: N.A

ISBN: 9780199456666

Category: Computer algorithms

Page: 692

View: 2437

Introduction To The Analysis Of Algorithms, An (3rd Edition)

Author: Soltys-kulinicz Michael

Publisher: World Scientific

ISBN: 9813235926

Category: Computers

Page: 328

View: 6118

A successor to the first and second editions, this updated and revised book is a leading companion guide for students and engineers alike, specifically software engineers who design algorithms. While succinct, this edition is mathematically rigorous, covering the foundations for both computer scientists and mathematicians with interest in the algorithmic foundations of Computer Science. Besides expositions on traditional algorithms such as Greedy, Dynamic Programming and Divide & Conquer, the book explores two classes of algorithms that are often overlooked in introductory textbooks: Randomised and Online algorithms — with emphasis placed on the algorithm itself. The book also covers algorithms in Linear Algebra, and the foundations of Computation. The coverage of Randomized and Online algorithms is timely: the former have become ubiquitous due to the emergence of cryptography, while the latter are essential in numerous fields as diverse as operating systems and stock market predictions. While being relatively short to ensure the essentiality of content, a strong focus has been placed on self-containment, introducing the idea of pre/post-conditions and loop invariants to readers of all backgrounds, as well as all the necessary mathematical foundations. The programming exercises in Python will be available on the web (see http: //www.msoltys.com/book for the companion web site). Contents: Preliminaries Greedy Algorithms Divide and Conquer Dynamic Programming Online Algorithms Randomized Algorithms Algorithms in Linear Algebra Computational Foundations Mathematical Foundations Readership: Students of undergraduate courses in algorithms and programming and associated professionals. Keywords: Algorithms;Greedy;Dynamic Programming;Online;Randomized;Loop InvariantReview:0

Introduction to Machine Learning

Author: Ethem Alpaydin

Publisher: MIT Press

ISBN: 0262028182

Category: Computers

Page: 640

View: 7699

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.