Search Results for "an-introduction-to-the-analysis-of-algorithms-2nd-edition"

An Introduction to the Analysis of Algorithms

An Introduction to the Analysis of Algorithms

  • Author: Robert Sedgewick,Philippe Flajolet
  • Publisher: Addison-Wesley
  • ISBN: 0133373487
  • Category: Computers
  • Page: 604
  • View: 4849
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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

An Introduction to the Analysis of Algorithms

An Introduction to the Analysis of Algorithms

  • Author: Michael Soltys
  • Publisher: World Scientific
  • ISBN: 981440117X
  • Category: Computers
  • Page: 212
  • View: 1530
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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

Introduction to the Design & Analysis of Algorithms

Introduction to the Design & Analysis of Algorithms

  • Author: Anany Levitin
  • Publisher: Addison-Wesley Longman
  • ISBN: 9780132316811
  • Category: Computers
  • Page: 565
  • View: 2428
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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

Introduction To Algorithms

  • Author: Thomas H.. Cormen,Thomas H Cormen,Charles E Leiserson,Ronald L Rivest,Clifford Stein
  • Publisher: MIT Press
  • ISBN: 9780262032933
  • Category: Computers
  • Page: 1180
  • View: 1257
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An extensively revised edition of a mathematically rigorous yet accessible introduction to algorithms.

Introduction To Design And Analysis Of Algorithms, 2/E

Introduction To Design And Analysis Of Algorithms, 2/E

  • Author: Levitin
  • Publisher: Pearson Education India
  • ISBN: 9788131718377
  • Category: Computer algorithms
  • Page: 544
  • View: 3613
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The Algorithm Design Manual: Text

The Algorithm Design Manual: Text

  • Author: Steven S. Skiena
  • Publisher: Springer Science & Business Media
  • ISBN: 9780387948607
  • Category: Computers
  • Page: 486
  • View: 3373
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This volume helps take some of the "mystery" out of identifying and dealing with key algorithms. Drawing heavily on the author's own real-world experiences, the book stresses design and analysis. Coverage is divided into two parts, the first being a general guide to techniques for the design and analysis of computer algorithms. The second is a reference section, which includes a catalog of the 75 most important algorithmic problems. By browsing this catalog, readers can quickly identify what the problem they have encountered is called, what is known about it, and how they should proceed if they need to solve it. This book is ideal for the working professional who uses algorithms on a daily basis and has need for a handy reference. This work can also readily be used in an upper-division course or as a student reference guide.THE ALGORITHM DESIGN MANUAL comes with a CD-ROM that contains:* a complete hypertext version of the full printed book.* the source code and URLs for all cited implementations.* over 30 hours of audio lectures on the design and analysis of algorithms are provided, all keyed to on-line lecture notes.

An Introduction to Kolmogorov Complexity and Its Applications

An Introduction to Kolmogorov Complexity and Its Applications

  • Author: Ming Li,Paul Vitanyi
  • Publisher: Springer Science & Business Media
  • ISBN: 1475738609
  • Category: Computers
  • Page: 550
  • View: 9786
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Analysis of Algorithms

Analysis of Algorithms

  • Author: Jeffrey McConnell
  • Publisher: Jones & Bartlett Publishers
  • ISBN: 0763787000
  • Category: Computers
  • Page: 451
  • View: 667
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Updated to follow the recommendations put forth by the ACM/SIGCSE 2001 task force, Analysis of Algorithms raises awareness of the effects that algorithms have on the efficiency of a program and develops the necessary skills to analyze general algorithms used in programs. The text presents the material with the expectation that it can be used with active and cooperative learning methodology, based on the premise that students learn more effectively and retain more information longer when they are active participants in the learning process. To accomplish this, the chapters are clear and complete to encourage students to prepare by reading before class, and the text is filled with exciting examples and exercises that look at the efficiency of various algorithms to solve a problem. The author is well known for workshops that he presents on the active learning model. He has written an instructor's manual that helps instructors understand how to present the material in an active way.

Introduction to Parallel Algorithms

Introduction to Parallel Algorithms

  • Author: C. Xavier,S. S. Iyengar
  • Publisher: John Wiley & Sons
  • ISBN: 9780471251828
  • Category: Computers
  • Page: 365
  • View: 850
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Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering.

DESIGN AND ANALYSIS OF ALGORITHMS

DESIGN AND ANALYSIS OF ALGORITHMS

  • Author: PRABHAKAR GUPTA,VINEET AGARWAL,MANISH VARSHNEY
  • Publisher: PHI Learning Pvt. Ltd.
  • ISBN: 8120346637
  • Category: Computers
  • Page: 424
  • View: 9850
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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

Introduction to the Theory of Computation

Introduction to the Theory of Computation

  • Author: Michael Sipser
  • Publisher: Cengage Learning
  • ISBN: 1285401069
  • Category: Computers
  • Page: 504
  • View: 4270
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Now you can clearly present even the most complex computational theory topics to your students with Sipser's distinct, market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today's computational theory course, this highly anticipated revision retains the unmatched clarity and thorough coverage that make it a leading text for upper-level undergraduate and introductory graduate students. This edition continues author Michael Sipser's well-known, approachable style with timely revisions, additional exercises, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. This edition's refined presentation ensures a trusted accuracy and clarity that make the challenging study of computational theory accessible and intuitive to students while maintaining the subject's rigor and formalism. Readers gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E's comprehensive coverage makes this an ideal ongoing reference tool for those studying theoretical computing. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Algorithm Design: Pearson New International Edition

Algorithm Design: Pearson New International Edition

  • Author: Jon Kleinberg,Eva Tardos
  • Publisher: Pearson Higher Ed
  • ISBN: 1292037040
  • Category: Computers
  • Page: 832
  • View: 7279
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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.

Analytic Combinatorics

Analytic Combinatorics

  • Author: Philippe Flajolet,Robert Sedgewick
  • Publisher: Cambridge University Press
  • ISBN: 1139477161
  • Category: Mathematics
  • Page: N.A
  • View: 1319
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Analytic combinatorics aims to enable precise quantitative predictions of the properties of large combinatorial structures. The theory has emerged over recent decades as essential both for the analysis of algorithms and for the study of scientific models in many disciplines, including probability theory, statistical physics, computational biology, and information theory. With a careful combination of symbolic enumeration methods and complex analysis, drawing heavily on generating functions, results of sweeping generality emerge that can be applied in particular to fundamental structures such as permutations, sequences, strings, walks, paths, trees, graphs and maps. This account is the definitive treatment of the topic. The authors give full coverage of the underlying mathematics and a thorough treatment of both classical and modern applications of the theory. The text is complemented with exercises, examples, appendices and notes to aid understanding. The book can be used for an advanced undergraduate or a graduate course, or for self-study.

Algorithms

Algorithms

  • Author: Robert Sedgewick,Kevin Wayne
  • Publisher: Addison-Wesley Professional
  • ISBN: 0133799107
  • Category: Computers
  • Page: 530
  • View: 7218
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This book is Part I of the fourth edition of Robert Sedgewick and Kevin Wayne’s Algorithms , the leading textbook on algorithms today, widely used in colleges and universities worldwide. Part I contains Chapters 1 through 3 of the book. The fourth edition of Algorithms surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use. The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts. The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants. Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Signal Processing for Neuroscientists

Signal Processing for Neuroscientists

  • Author: Wim van Drongelen
  • Publisher: Academic Press
  • ISBN: 012810483X
  • Category: Science
  • Page: 740
  • View: 7007
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Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications in neuronal modeling. It features nine new chapters and an exercise section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics using identical or similar mathematics presents a didactic advantage and a significant resource for neuroscientists with quantitative interest. Although each of the topics introduced could fill several volumes, this book provides a fundamental and uncluttered background for the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing and modeling. Includes an introduction to biomedical signals, noise characteristics, recording techniques, and the more advanced topics of linear, nonlinear and multi-channel systems analysis Features new chapters on the fundamentals of modeling, application to neuronal modeling, Kalman filter, multi-taper power spectrum estimation, and practice exercises Contains the basics and background for more advanced topics in extensive notes and appendices Includes practical examples of algorithm development and implementation in MATLAB Features a companion website with MATLAB scripts, data files, figures and video lectures

Artificial Intelligence

Artificial Intelligence

With an Introduction to Machine Learning, Second Edition

  • Author: Richard E. Neapolitan,Xia Jiang
  • Publisher: CRC Press
  • ISBN: 1351384392
  • Category: Computers
  • Page: 466
  • View: 8285
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The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods. The book is divided into five sections that focus on the most useful techniques that have emerged from AI. The first section of the book covers logic-based methods, while the second section focuses on probability-based methods. Emergent intelligence is featured in the third section and explores evolutionary computation and methods based on swarm intelligence. The newest section comes next and provides a detailed overview of neural networks and deep learning. The final section of the book focuses on natural language understanding. Suitable for undergraduate and beginning graduate students, this class-tested textbook provides students and other readers with key AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more.

Introduction to Programming in Java

Introduction to Programming in Java

An Interdisciplinary Approach

  • Author: Robert Sedgewick,Kevin Wayne
  • Publisher: Addison-Wesley Professional
  • ISBN: 0134511603
  • Category: Computers
  • Page: 784
  • View: 4144
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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.

Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications

  • Author: Robert Nisbet,Gary Miner,Ken Yale
  • Publisher: Elsevier
  • ISBN: 0124166458
  • Category: Mathematics
  • Page: 822
  • View: 1383
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Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. Includes input by practitioners for practitioners Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models Contains practical advice from successful real-world implementations Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

A Wavelet Tour of Signal Processing

A Wavelet Tour of Signal Processing

The Sparse Way

  • Author: Stephane Mallat
  • Publisher: Academic Press
  • ISBN: 9780080922027
  • Category: Technology & Engineering
  • Page: 832
  • View: 9577
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Mallat's book is the undisputed reference in this field - it is the only one that covers the essential material in such breadth and depth. - Laurent Demanet, Stanford University The new edition of this classic book gives all the major concepts, techniques and applications of sparse representation, reflecting the key role the subject plays in today's signal processing. The book clearly presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms. The central concept of sparsity is explained and applied to signal compression, noise reduction, and inverse problems, while coverage is given to sparse representations in redundant dictionaries, super-resolution and compressive sensing applications. Features: * Balances presentation of the mathematics with applications to signal processing * Algorithms and numerical examples are implemented in WaveLab, a MATLAB toolbox New in this edition * Sparse signal representations in dictionaries * Compressive sensing, super-resolution and source separation * Geometric image processing with curvelets and bandlets * Wavelets for computer graphics with lifting on surfaces * Time-frequency audio processing and denoising * Image compression with JPEG-2000 * New and updated exercises A Wavelet Tour of Signal Processing: The Sparse Way, Third Edition, is an invaluable resource for researchers and R&D engineers wishing to apply the theory in fields such as image processing, video processing and compression, bio-sensing, medical imaging, machine vision and communications engineering. Stephane Mallat is Professor in Applied Mathematics at École Polytechnique, Paris, France. From 1986 to 1996 he was a Professor at the Courant Institute of Mathematical Sciences at New York University, and between 2001 and 2007, he co-founded and became CEO of an image processing semiconductor company. Includes all the latest developments since the book was published in 1999, including its application to JPEG 2000 and MPEG-4 Algorithms and numerical examples are implemented in Wavelab, a MATLAB toolbox Balances presentation of the mathematics with applications to signal processing