Introduction to Matrix Computations
Introduction to Matrix Computations

Author: G. W. Stewart

Publisher: Elsevier

Published: 1973-06-15

Total Pages: 457

ISBN-13: 0080926142

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Numerical linear algebra is far too broad a subject to treat in a single introductory volume. Stewart has chosen to treat algorithms for solving linear systems, linear least squares problems, and eigenvalue problems involving matrices whose elements can all be contained in the high-speed storage of a computer. By way of theory, the author has chosen to discuss the theory of norms and perturbation theory for linear systems and for the algebraic eigenvalue problem. These choices exclude, among other things, the solution of large sparse linear systems by direct and iterative methods, linear programming, and the useful Perron-Frobenious theory and its extensions. However, a person who has fully mastered the material in this book should be well prepared for independent study in other areas of numerical linear algebra.

Handbook for Matrix Computations
Handbook for Matrix Computations

Author: Thomas F. Coleman

Publisher: SIAM

Published: 1988-01-01

Total Pages: 271

ISBN-13: 9781611971040

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Provides the user with a step-by-step introduction to Fortran 77, BLAS, LINPACK, and MATLAB. It is a reference that spans several levels of practical matrix computations with a strong emphasis on examples and "hands on" experience.

Introduction to Applied Linear Algebra
Introduction to Applied Linear Algebra

Author: Stephen Boyd

Publisher: Cambridge University Press

Published: 2018-06-07

Total Pages: 477

ISBN-13: 1316518965

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A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Linear Algebra and Matrix Computations with MATLAB®
Linear Algebra and Matrix Computations with MATLAB®

Author: Dingyü Xue

Publisher: Walter de Gruyter GmbH & Co KG

Published: 2020-03-23

Total Pages: 361

ISBN-13: 3110663716

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This book focuses the solutions of linear algebra and matrix analysis problems, with the exclusive use of MATLAB. The topics include representations, fundamental analysis, transformations of matrices, matrix equation solutions as well as matrix functions. Attempts on matrix and linear algebra applications are also explored.

Numerical Methods in Matrix Computations
Numerical Methods in Matrix Computations

Author: Åke Björck

Publisher: Springer

Published: 2014-10-07

Total Pages: 812

ISBN-13: 3319050893

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Matrix algorithms are at the core of scientific computing and are indispensable tools in most applications in engineering. This book offers a comprehensive and up-to-date treatment of modern methods in matrix computation. It uses a unified approach to direct and iterative methods for linear systems, least squares and eigenvalue problems. A thorough analysis of the stability, accuracy, and complexity of the treated methods is given. Numerical Methods in Matrix Computations is suitable for use in courses on scientific computing and applied technical areas at advanced undergraduate and graduate level. A large bibliography is provided, which includes both historical and review papers as well as recent research papers. This makes the book useful also as a reference and guide to further study and research work.

Introduction to Computational Linear Algebra
Introduction to Computational Linear Algebra

Author: Nabil Nassif

Publisher: CRC Press

Published: 2015-06-24

Total Pages: 258

ISBN-13: 1482258714

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Teach Your Students Both the Mathematics of Numerical Methods and the Art of Computer ProgrammingIntroduction to Computational Linear Algebra presents classroom-tested material on computational linear algebra and its application to numerical solutions of partial and ordinary differential equations. The book is designed for senior undergraduate stud

Matrix Algebra
Matrix Algebra

Author: James E. Gentle

Publisher: Springer Science & Business Media

Published: 2007-07-27

Total Pages: 536

ISBN-13: 0387708723

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Matrix algebra is one of the most important areas of mathematics for data analysis and for statistical theory. This much-needed work presents the relevant aspects of the theory of matrix algebra for applications in statistics. It moves on to consider the various types of matrices encountered in statistics, such as projection matrices and positive definite matrices, and describes the special properties of those matrices. Finally, it covers numerical linear algebra, beginning with a discussion of the basics of numerical computations, and following up with accurate and efficient algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors.

Matrices, Moments and Quadrature with Applications
Matrices, Moments and Quadrature with Applications

Author: Gene H. Golub

Publisher: Princeton University Press

Published: 2009-12-07

Total Pages: 376

ISBN-13: 1400833884

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This computationally oriented book describes and explains the mathematical relationships among matrices, moments, orthogonal polynomials, quadrature rules, and the Lanczos and conjugate gradient algorithms. The book bridges different mathematical areas to obtain algorithms to estimate bilinear forms involving two vectors and a function of the matrix. The first part of the book provides the necessary mathematical background and explains the theory. The second part describes the applications and gives numerical examples of the algorithms and techniques developed in the first part. Applications addressed in the book include computing elements of functions of matrices; obtaining estimates of the error norm in iterative methods for solving linear systems and computing parameters in least squares and total least squares; and solving ill-posed problems using Tikhonov regularization. This book will interest researchers in numerical linear algebra and matrix computations, as well as scientists and engineers working on problems involving computation of bilinear forms.

Matrix Algebra From a Statistician's Perspective
Matrix Algebra From a Statistician's Perspective

Author: David A. Harville

Publisher: Springer Science & Business Media

Published: 2008-06-27

Total Pages: 639

ISBN-13: 0387783563

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A knowledge of matrix algebra is a prerequisite for the study of much of modern statistics, especially the areas of linear statistical models and multivariate statistics. This reference book provides the background in matrix algebra necessary to do research and understand the results in these areas. Essentially self-contained, the book is best-suited for a reader who has had some previous exposure to matrices. Solultions to the exercises are available in the author's "Matrix Algebra: Exercises and Solutions."