Essential Algorithms

Author: Rod Stephens
Publisher: John Wiley & Sons
ISBN: 1118797299
Format: PDF, ePub, Mobi
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A friendly and accessible introduction to the most useful algorithms Computer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve difficult programming problems. Written in simple, intuitive English, this book describes how and when to use the most practical classic algorithms, and even how to create new algorithms to meet future needs. The book also includes a collection of questions that can help readers prepare for a programming job interview. Reveals methods for manipulating common data structures such as arrays, linked lists, trees, and networks Addresses advanced data structures such as heaps, 2-3 trees, B-trees Addresses general problem-solving techniques such as branch and bound, divide and conquer, recursion, backtracking, heuristics, and more Reviews sorting and searching, network algorithms, and numerical algorithms Includes general problem-solving techniques such as brute force and exhaustive search, divide and conquer, backtracking, recursion, branch and bound, and more In addition, Essential Algorithms features a companion website that includes full instructor materials to support training or higher ed adoptions.

Essential Algorithms

Author: Rod Stephens
Publisher: John Wiley & Sons
ISBN: 1118612108
Format: PDF, Docs
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Exercises; Chapter 18: Distributed Algorithms; Types of Parallelism; Distributed Algorithms; Summary; Exercises; Chapter 19: Interview Puzzles; Asking Interview Puzzle Questions; Answering Interview Puzzle Questions; Summary; Exercises; Appendix A: Summary of Algorithmic Concepts; Chapter 1: Algorithm Basics; Chapter 2: Numeric Algorithms; Chapter 3: Linked Lists; Chapter 4: Arrays; Chapter 5: Stacks and Queues; Chapter 6: Sorting; Chapter 7: Searching; Chapter 8: Hash Tables; Chapter 9: Recursion; Chapter 10: Trees; Chapter 11: Balanced Trees; Chapter 12: Decision Trees.

Practical Analysis of Algorithms

Author: Dana Vrajitoru
Publisher: Springer
ISBN: 3319098888
Format: PDF, Kindle
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This book introduces the essential concepts of algorithm analysis required by core undergraduate and graduate computer science courses, in addition to providing a review of the fundamental mathematical notions necessary to understand these concepts. Features: includes numerous fully-worked examples and step-by-step proofs, assuming no strong mathematical background; describes the foundation of the analysis of algorithms theory in terms of the big-Oh, Omega, and Theta notations; examines recurrence relations; discusses the concepts of basic operation, traditional loop counting, and best case and worst case complexities; reviews various algorithms of a probabilistic nature, and uses elements of probability theory to compute the average complexity of algorithms such as Quicksort; introduces a variety of classical finite graph algorithms, together with an analysis of their complexity; provides an appendix on probability theory, reviewing the major definitions and theorems used in the book.

The Algorithm Design Manual

Author: Steven S Skiena
Publisher: Springer Science & Business Media
ISBN: 1848000707
Format: PDF, ePub, Mobi
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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

Algorithms Unplugged

Author: Berthold Vöcking
Publisher: Springer Science & Business Media
ISBN: 9783642153280
Format: PDF
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Algorithms specify the way computers process information and how they execute tasks. Many recent technological innovations and achievements rely on algorithmic ideas – they facilitate new applications in science, medicine, production, logistics, traffic, communi¬cation and entertainment. Efficient algorithms not only enable your personal computer to execute the newest generation of games with features unimaginable only a few years ago, they are also key to several recent scientific breakthroughs – for example, the sequencing of the human genome would not have been possible without the invention of new algorithmic ideas that speed up computations by several orders of magnitude. The greatest improvements in the area of algorithms rely on beautiful ideas for tackling computational tasks more efficiently. The problems solved are not restricted to arithmetic tasks in a narrow sense but often relate to exciting questions of nonmathematical flavor, such as: How can I find the exit out of a maze? How can I partition a treasure map so that the treasure can only be found if all parts of the map are recombined? How should I plan my trip to minimize cost? Solving these challenging problems requires logical reasoning, geometric and combinatorial imagination, and, last but not least, creativity – the skills needed for the design and analysis of algorithms. In this book we present some of the most beautiful algorithmic ideas in 41 articles written in colloquial, nontechnical language. Most of the articles arose out of an initiative among German-language universities to communicate the fascination of algorithms and computer science to high-school students. The book can be understood without any prior knowledge of algorithms and computing, and it will be an enlightening and fun read for students and interested adults.

Compact Data Structures

Author: Gonzalo Navarro
Publisher: Cambridge University Press
ISBN: 1316791009
Format: PDF, Mobi
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Compact data structures help represent data in reduced space while allowing it to be queried, navigated, and operated in compressed form. They are essential tools for efficiently handling massive amounts of data by exploiting the memory hierarchy. They also reduce the resources needed in distributed deployments and make better use of the limited memory in low-end devices. The field has developed rapidly, reaching a level of maturity that allows practitioners and researchers in application areas to benefit from the use of compact data structures. This first comprehensive book on the topic focuses on the structures that are most relevant for practical use. Readers will learn how the structures work, how to choose the right ones for their application scenario, and how to implement them. Researchers and students in the area will find in the book a definitive guide to the state of the art in compact data structures.

Algorithms

Author: Fethi Rabhi
Publisher: Addison Wesley
ISBN: 9780201596045
Format: PDF, Mobi
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A student introduction to the design of algorithms for problem solving. Written from a functional programming perspective, the text should appeal to anyone studying algorithms. Included are end-of-chapter exercises and bibliographic references.

Algorithms to Live By

Author: Brian Christian
Publisher: Macmillan
ISBN: 1627790365
Format: PDF, Docs
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A fascinating exploration of how insights from computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind All our lives are constrained by limited space and time, limits that give rise to a particular set of problems. What should we do, or leave undone, in a day or a lifetime? How much messiness should we accept? What balance of new activities and familiar favorites is the most fulfilling? These may seem like uniquely human quandaries, but they are not: computers, too, face the same constraints, so computer scientists have been grappling with their version of such issues for decades. And the solutions they've found have much to teach us. In a dazzlingly interdisciplinary work, acclaimed author Brian Christian and cognitive scientist Tom Griffiths show how the algorithms used by computers can also untangle very human questions. They explain how to have better hunches and when to leave things to chance, how to deal with overwhelming choices and how best to connect with others. From finding a spouse to finding a parking spot, from organizing one's inbox to understanding the workings of memory, Algorithms to Live By transforms the wisdom of computer science into strategies for human living.

Beginning Algorithms

Author: Simon Harris
Publisher: John Wiley & Sons
ISBN: 9780470329726
Format: PDF
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Beginning Algorithms A good understanding of algorithms, and the knowledge of when to apply them, is crucial to producing software that not only works correctly, but also performs efficiently. This is the only book to impart all this essential information-from the basics of algorithms, data structures, and performance characteristics to the specific algorithms used in development and programming tasks. Packed with detailed explanations and instructive examples, the book begins by offering you some fundamental data structures and then goes on to explain various sorting algorithms. You'll then learn efficient practices for storing and searching by way of hashing, trees, sets, and maps. The authors also share tips on optimization techniques and ways to avoid common performance pitfalls. In the end, you'll be prepared to build the algorithms and data structures most commonly encountered in day-to-day software development. What you will learn from this book The basics of algorithms, such as iteration and recursion Elementary data structures such as lists, stacks, and queues Basic and advanced sorting algorithms including insertion sort, quicksort, and shell sort Advanced data structures such as binary trees, ternary trees, and heaps Algorithms for string searching, string matching, hashing, and computational geometry How to use test-driven development techniques to ensure your code works as intended How to dramatically improve the performance of your code with hands-on techniques for profiling and optimization Who this book is for This book is for anyone who develops applications, or is just beginning to do so, and is looking to understand algorithms and data structures. An understanding of computer programming is beneficial. Wrox Beginning guides are crafted to make learning programming languages and technologies easier than you think, providing a structured, tutorial format that will guide you through all the techniques involved.

Differential Evolution

Author: Kenneth Price
Publisher: Springer Science & Business Media
ISBN: 3540313060
Format: PDF, Kindle
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Problems demanding globally optimal solutions are ubiquitous, yet many are intractable when they involve constrained functions having many local optima and interacting, mixed-type variables. The differential evolution (DE) algorithm is a practical approach to global numerical optimization which is easy to understand, simple to implement, reliable, and fast. Packed with illustrations, computer code, new insights, and practical advice, this volume explores DE in both principle and practice. It is a valuable resource for professionals needing a proven optimizer and for students wanting an evolutionary perspective on global numerical optimization.