Introduction Algorithms (Over 2,000 results)

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Computer Algorithms: Introduction to Design and Analysis (Addison-Wesley Series in Computer Science)
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Computer Algorithms: Introduction to Design and Analysis (Addison-Wesley Series in Computer Science)
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Language: English
Published by The MIT Press, 2004
- Hardcover
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Computer Algorithms: Introduction to Design and Analysis (Addison-Wesley Series in Computer Science)
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Language: English
Published by MIT Press Ltd, 2004
- Hardcover
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
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Hardback. Condition: Good. An introductory text that emphasizes the underlying algorithmic ideas that are driving advances in bioinformatics. This introductory text offers a clear exposition of the algorithmic principles driving advances in bioinformatics. Accessible to students in both biology and computer science, it strikes a unique balance between rigorous mathematics and practical techniques, emphasizing the ideas underlying algorithms rather than offering a collection of apparently unrelated problems. The book introduces biological and algorithmic ideas together, linking issues in computer science to biology and thus capturing the interest of students in both subjects. It demonstrates that relatively few design techniques can be used to solve a large number of practical problems in biology, and presents this material intuitively. An Introduction to Bioinformatics Algorithms is one of the first books on bioinformatics that can be used by students at an undergraduate level. It includes a dual table of contents, organized by algorithmic idea and biological idea; discussions of biologically relevant problems, including a detailed problem formulation and one or more solutions for each; and brief biographical sketches of leading figures in the field. These interesting vignettes offer students a glimpse of the inspirations and motivations for real work in bioinformatics, making the concepts presented in the text more concrete and the techniques more approachable.PowerPoint presentations, practical bioinformatics problems, sample code, diagrams, demonstrations, and other materials can be found at the Author's website.…

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Condition: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: Second ] Publisher: Cram101 Inc. Pub Date: 1/1/2010 Binding: Paperback Pages: 230 Second edition.

- Softcover
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Paperback. Condition: Very Good. This is an innovative new book designed to teach algorithmic approaches to solving engineering problems. De-emphasizing syntax, the author focuses on structured approaches to implementing solutions using a subset of the C++ language. It focuses on developing common algorithmic patterns and how to use them to solve complex problems. Engineering applications requiring use of algebra, calculus, and physics are also included in this book.…

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Paperback. Condition: Fair. Drawing upon combined decades of teaching experience, Professors Sara Baase and Allen Van Gelder have extensively revised this best seller to make it the most current and accessible choice for any algorithms course. The new Third Edition features the addition of new topics and exercises and an increased emphasis on algorithm design techniques such as divide-and-conquer and greedy algorithms. It continues the tradition of solid mathematical analysis and clear writing style that made it so popular in previous editions.…

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Paperback. Condition: Good. Genetic algorithms have been used in science and engineering as adaptive algorithms for solving practical problems and as computational models of natural evolutionary systems. This brief, accessible introduction describes some of the most interesting research in the field and also enables readers to implement and experiment with genetic algorithms on their own. It focuses in depth on a small set of important and interesting topics--particularly in machine learning, scientific modeling, and artificial life--and reviews a broad span of research, including the work of Mitchell and her colleagues.The descriptions of applications and modeling projects stretch beyond the strict boundaries of computer science to include dynamical systems theory, game theory, molecular biology, ecology, evolutionary biology, and population genetics, underscoring the exciting general purpose nature of genetic algorithms as search methods that can be employed across disciplines.An Introduction to Genetic Algorithms is accessible to students and researchers in any scientific discipline. It includes many thought and computer exercises that build on and reinforce the reader's understanding of the text. The first chapter introduces genetic algorithms and their terminology and describes two provocative applications in detail. The second and third chapters look at the use of genetic algorithms in machine learning (computer programs, data analysis and prediction, neural networks) and in scientific models (interactions among learning, evolution, and culture; sexual selection; ecosystems; evolutionary activity). Several approaches to the theory of genetic algorithms are discussed in depth in the fourth chapter. The fifth chapter takes up implementation, and the last chapter poses some currently unanswered questions and surveys prospects for the future of evolutionary computation.…

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