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Author: Richard L. Burden Publisher: Cengage Learning ISBN: 9780534392024 Category : Mathematics Languages : en Pages : 213
Book Description
The Student Solutions Manual contains worked-out solutions to many of the problems. It also illustrates the calls required for the programs using the algorithms in the text, which is especially useful for those with limited programming experience.
Author: Ian H. Hutchinson Publisher: Cambridge University Press ISBN: 1107095670 Category : Computers Languages : en Pages : 223
Book Description
The plain language style, worked examples and exercises in this book help students to understand the foundations of computational physics and engineering.
Author: Steven C. Chapra Publisher: McGraw-Hill Science/Engineering/Math ISBN: Category : Computers Languages : en Pages : 618
Book Description
Still brief - but with the chapters that you wanted - Steven Chapra’s new second edition is written for engineering and science students who need to learn numerical problem solving. This text focuses on problem-solving applications rather than theory, using MATLAB throughout. Theory is introduced to inform key concepts which are framed in applications and demonstrated using MATLAB. The new second edition feature new chapters on Numerical Differentiation, Optimization, and Boundary-Value Problems (ODEs).
Author: Walter Rudin Publisher: McGraw-Hill Publishing Company ISBN: 9780070856134 Category : Mathematics Languages : en Pages : 342
Book Description
The third edition of this well known text continues to provide a solid foundation in mathematical analysis for undergraduate and first-year graduate students. The text begins with a discussion of the real number system as a complete ordered field. (Dedekind's construction is now treated in an appendix to Chapter I.) The topological background needed for the development of convergence, continuity, differentiation and integration is provided in Chapter 2. There is a new section on the gamma function, and many new and interesting exercises are included. This text is part of the Walter Rudin Student Series in Advanced Mathematics.
Author: Erwin Kreyszig Publisher: Wiley ISBN: 9780471726449 Category : Mathematics Languages : en Pages : 260
Book Description
This market leading text is known for its comprehensive coverage, careful and correct mathematics, outstanding exercises and self contained subject matter parts for maximum flexibility. Thoroughly updated and streamlined to reflect new developments in the field, the ninth edition of this bestselling text features modern engineering applications and the uses of technology. Kreyszig introduces engineers and computer scientists to advanced math topics as they relate to practical problems. The material is arranged into seven independent parts: ODE; Linear Algebra, Vector Calculus; Fourier Analysis and Partial Differential Equations; Complex Analysis; Numerical methods; Optimization, graphs; and Probability and Statistics.
Author: Stephen Boyd Publisher: Cambridge University Press ISBN: 1316518965 Category : Business & Economics Languages : en Pages : 477
Book Description
A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.
Author: J. Lewis Blackburn Publisher: CRC Press ISBN: 1439888124 Category : Technology & Engineering Languages : en Pages : 678
Book Description
For many years, Protective Relaying: Principles and Applications has been the go-to text for gaining proficiency in the technological fundamentals of power system protection. Continuing in the bestselling tradition of the previous editions by the late J. Lewis Blackburn, the Fourth Edition retains the core concepts at the heart of power system anal
Author: J. Douglas Faires Publisher: Brooks Cole ISBN: Category : Mathematics Languages : en Pages : 616
Book Description
This text emphasizes the intelligent application of approximation techniques to the type of problems that commonly occur in engineering and the physical sciences. The authors provide a sophisticated introduction to various appropriate approximation techniques; they show students why the methods work, what type of errors to expect, and when an application might lead to difficulties; and they provide information about the availability of high-quality software for numerical approximation routines The techniques covered in this text are essentially the same as those covered in the Sixth Edition of these authors' top-selling Numerical Analysis text, but the emphasis is much different. In Numerical Methods, Second Edition, full mathematical justifications are provided only if they are concise and add to the understanding of the methods. The emphasis is placed on describing each technique from an implementation standpoint, and on convincing the student that the method is reasonable both mathematically and computationally.
Author: Trevor Hastie Publisher: Springer Science & Business Media ISBN: 0387216065 Category : Mathematics Languages : en Pages : 545
Book Description
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.
Author: Richard L. Burden
Author: Richard L. Burden
Author: Richard L. Burden
Author: Ian H. Hutchinson
Author: Steven C. Chapra
Author: Walter Rudin
Author: Erwin Kreyszig
Author: Stephen Boyd
Author: J. Lewis Blackburn
Author: J. Douglas Faires
Author: Trevor Hastie