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Scientific Computing with Case Studies

2009-03-19 Mathematics
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Release : 2009-03-19
Genre : Mathematics
Kind : eBook
Book Rating : 667/5 ( reviews)

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Book Synopsis Scientific Computing with Case Studies by : Dianne P. O'Leary

Download or read book Scientific Computing with Case Studies written by Dianne P. O'Leary. This book was released on 2009-03-19. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.

Scientific Computing with Case Studies

2009-01-01 Mathematics
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Release : 2009-01-01
Genre : Mathematics
Kind : eBook
Book Rating : 728/5 ( reviews)

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Book Synopsis Scientific Computing with Case Studies by : Dianne P. O'Leary

Download or read book Scientific Computing with Case Studies written by Dianne P. O'Leary. This book was released on 2009-01-01. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.

Scientific Computing

2018-11-14 Science
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Release : 2018-11-14
Genre : Science
Kind : eBook
Book Rating : 573/5 ( reviews)

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Book Synopsis Scientific Computing by : Michael T. Heath

Download or read book Scientific Computing written by Michael T. Heath. This book was released on 2018-11-14. Available in PDF, EPUB and Kindle. Book excerpt: This book differs from traditional numerical analysis texts in that it focuses on the motivation and ideas behind the algorithms presented rather than on detailed analyses of them. It presents a broad overview of methods and software for solving mathematical problems arising in computational modeling and data analysis, including proper problem formulation, selection of effective solution algorithms, and interpretation of results.? In the 20 years since its original publication, the modern, fundamental perspective of this book has aged well, and it continues to be used in the classroom. This Classics edition has been updated to include pointers to Python software and the Chebfun package, expansions on barycentric formulation for Lagrange polynomial interpretation and stochastic methods, and the availability of about 100 interactive educational modules that dynamically illustrate the concepts and algorithms in the book. Scientific Computing: An Introductory Survey, Second Edition is intended as both a textbook and a reference for computationally oriented disciplines that need to solve mathematical problems.

Data Science in R

2015-04-21 Business & Economics
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Release : 2015-04-21
Genre : Business & Economics
Kind : eBook
Book Rating : 823/5 ( reviews)

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Book Synopsis Data Science in R by : Deborah Nolan

Download or read book Data Science in R written by Deborah Nolan. This book was released on 2015-04-21. Available in PDF, EPUB and Kindle. Book excerpt: Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and ComputationData Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts

Scientific Computing

2018-05-14 Mathematics
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Release : 2018-05-14
Genre : Mathematics
Kind : eBook
Book Rating : 058/5 ( reviews)

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Book Synopsis Scientific Computing by : John A. Trangenstein

Download or read book Scientific Computing written by John A. Trangenstein. This book was released on 2018-05-14. Available in PDF, EPUB and Kindle. Book excerpt: This is the first of three volumes providing a comprehensive presentation of the fundamentals of scientific computing. This volume discusses basic principles of computation, and fundamental numerical algorithms that will serve as basic tools for the subsequent two volumes. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses programming in several languages, including C++, Fortran and MATLAB. There are 80 examples, 324 exercises, 77 algorithms, 35 interactive JavaScript programs, 391 references to software programs and 4 case studies. Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB. This book could be used for an introductory course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as principles of computer languages or numerical linear algebra.

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