Introduction to Matrix Analysis and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 3319041509
Total Pages : 337 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Introduction to Matrix Analysis and Applications by : Fumio Hiai

Download or read book Introduction to Matrix Analysis and Applications written by Fumio Hiai and published by Springer Science & Business Media. This book was released on 2014-02-06 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrices can be studied in different ways. They are a linear algebraic structure and have a topological/analytical aspect (for example, the normed space of matrices) and they also carry an order structure that is induced by positive semidefinite matrices. The interplay of these closely related structures is an essential feature of matrix analysis. This book explains these aspects of matrix analysis from a functional analysis point of view. After an introduction to matrices and functional analysis, it covers more advanced topics such as matrix monotone functions, matrix means, majorization and entropies. Several applications to quantum information are also included. Introduction to Matrix Analysis and Applications is appropriate for an advanced graduate course on matrix analysis, particularly aimed at studying quantum information. It can also be used as a reference for researchers in quantum information, statistics, engineering and economics.

Introduction to Matrix Analysis

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Publisher : SIAM
ISBN 13 : 0898713994
Total Pages : 424 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Introduction to Matrix Analysis by : Richard Bellman

Download or read book Introduction to Matrix Analysis written by Richard Bellman and published by SIAM. This book was released on 1997-12-01 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lucid and concise, this volume covers all the key aspects of matrix analysis and presents a variety of fundamental methods.

Introduction to Matrix Theory

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Author :
Publisher : Springer Nature
ISBN 13 : 303080481X
Total Pages : 199 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Introduction to Matrix Theory by : Arindama Singh

Download or read book Introduction to Matrix Theory written by Arindama Singh and published by Springer Nature. This book was released on 2021-08-16 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed to serve as a textbook for courses offered to undergraduate and postgraduate students enrolled in Mathematics. Using elementary row operations and Gram-Schmidt orthogonalization as basic tools the text develops characterization of equivalence and similarity, and various factorizations such as rank factorization, OR-factorization, Schurtriangularization, Diagonalization of normal matrices, Jordan decomposition, singular value decomposition, and polar decomposition. Along with Gauss-Jordan elimination for linear systems, it also discusses best approximations and least-squares solutions. The book includes norms on matrices as a means to deal with iterative solutions of linear systems and exponential of a matrix. The topics in the book are dealt with in a lively manner. Each section of the book has exercises to reinforce the concepts, and problems have been added at the end of each chapter. Most of these problems are theoretical, and they do not fit into the running text linearly. The detailed coverage and pedagogical tools make this an ideal textbook for students and researchers enrolled in senior undergraduate and beginning postgraduate mathematics courses.

Matrix Analysis for Statistics

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Publisher : John Wiley & Sons
ISBN 13 : 1119092485
Total Pages : 547 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Matrix Analysis for Statistics by : James R. Schott

Download or read book Matrix Analysis for Statistics written by James R. Schott and published by John Wiley & Sons. This book was released on 2016-06-20 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date version of the complete, self-contained introduction to matrix analysis theory and practice Providing accessible and in-depth coverage of the most common matrix methods now used in statistical applications, Matrix Analysis for Statistics, Third Edition features an easy-to-follow theorem/proof format. Featuring smooth transitions between topical coverage, the author carefully justifies the step-by-step process of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; and the distribution of quadratic forms. An ideal introduction to matrix analysis theory and practice, Matrix Analysis for Statistics, Third Edition features: • New chapter or section coverage on inequalities, oblique projections, and antieigenvalues and antieigenvectors • Additional problems and chapter-end practice exercises at the end of each chapter • Extensive examples that are familiar and easy to understand • Self-contained chapters for flexibility in topic choice • Applications of matrix methods in least squares regression and the analyses of mean vectors and covariance matrices Matrix Analysis for Statistics, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses on matrix methods, multivariate analysis, and linear models. The book is also an excellent reference for research professionals in applied statistics. James R. Schott, PhD, is Professor in the Department of Statistics at the University of Central Florida. He has published numerous journal articles in the area of multivariate analysis. Dr. Schott’s research interests include multivariate analysis, analysis of covariance and correlation matrices, and dimensionality reduction techniques.

Fundamentals of Matrix Analysis with Applications

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Publisher : John Wiley & Sons
ISBN 13 : 1118953657
Total Pages : 407 pages
Book Rating : 4.1/5 (189 download)

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Book Synopsis Fundamentals of Matrix Analysis with Applications by : Edward Barry Saff

Download or read book Fundamentals of Matrix Analysis with Applications written by Edward Barry Saff and published by John Wiley & Sons. This book was released on 2015-10-12 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible and clear introduction to linear algebra with a focus on matrices and engineering applications Providing comprehensive coverage of matrix theory from a geometric and physical perspective, Fundamentals of Matrix Analysis with Applications describes the functionality of matrices and their ability to quantify and analyze many practical applications. Written by a highly qualified author team, the book presents tools for matrix analysis and is illustrated with extensive examples and software implementations. Beginning with a detailed exposition and review of the Gauss elimination method, the authors maintain readers’ interest with refreshing discussions regarding the issues of operation counts, computer speed and precision, complex arithmetic formulations, parameterization of solutions, and the logical traps that dictate strict adherence to Gauss’s instructions. The book heralds matrix formulation both as notational shorthand and as a quantifier of physical operations such as rotations, projections, reflections, and the Gauss reductions. Inverses and eigenvectors are visualized first in an operator context before being addressed computationally. Least squares theory is expounded in all its manifestations including optimization, orthogonality, computational accuracy, and even function theory. Fundamentals of Matrix Analysis with Applications also features: Novel approaches employed to explicate the QR, singular value, Schur, and Jordan decompositions and their applications Coverage of the role of the matrix exponential in the solution of linear systems of differential equations with constant coefficients Chapter-by-chapter summaries, review problems, technical writing exercises, select solutions, and group projects to aid comprehension of the presented concepts Fundamentals of Matrix Analysis with Applications is an excellent textbook for undergraduate courses in linear algebra and matrix theory for students majoring in mathematics, engineering, and science. The book is also an accessible go-to reference for readers seeking clarification of the fine points of kinematics, circuit theory, control theory, computational statistics, and numerical algorithms.

Introduction to Linear and Matrix Algebra

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Publisher : Springer Nature
ISBN 13 : 3030528111
Total Pages : 482 pages
Book Rating : 4.0/5 (35 download)

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Book Synopsis Introduction to Linear and Matrix Algebra by : Nathaniel Johnston

Download or read book Introduction to Linear and Matrix Algebra written by Nathaniel Johnston and published by Springer Nature. This book was released on 2021-05-19 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook emphasizes the interplay between algebra and geometry to motivate the study of linear algebra. Matrices and linear transformations are presented as two sides of the same coin, with their connection motivating inquiry throughout the book. By focusing on this interface, the author offers a conceptual appreciation of the mathematics that is at the heart of further theory and applications. Those continuing to a second course in linear algebra will appreciate the companion volume Advanced Linear and Matrix Algebra. Starting with an introduction to vectors, matrices, and linear transformations, the book focuses on building a geometric intuition of what these tools represent. Linear systems offer a powerful application of the ideas seen so far, and lead onto the introduction of subspaces, linear independence, bases, and rank. Investigation then focuses on the algebraic properties of matrices that illuminate the geometry of the linear transformations that they represent. Determinants, eigenvalues, and eigenvectors all benefit from this geometric viewpoint. Throughout, “Extra Topic” sections augment the core content with a wide range of ideas and applications, from linear programming, to power iteration and linear recurrence relations. Exercises of all levels accompany each section, including many designed to be tackled using computer software. Introduction to Linear and Matrix Algebra is ideal for an introductory proof-based linear algebra course. The engaging color presentation and frequent marginal notes showcase the author’s visual approach. Students are assumed to have completed one or two university-level mathematics courses, though calculus is not an explicit requirement. Instructors will appreciate the ample opportunities to choose topics that align with the needs of each classroom, and the online homework sets that are available through WeBWorK.

Matrix Analysis and Applications

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Publisher : Cambridge University Press
ISBN 13 : 1108417418
Total Pages : 761 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Matrix Analysis and Applications by : Xian-Da Zhang

Download or read book Matrix Analysis and Applications written by Xian-Da Zhang and published by Cambridge University Press. This book was released on 2017-10-05 with total page 761 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theory, methods and applications of matrix analysis are presented here in a novel theoretical framework.

Matrix Theory

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Publisher : Springer Science & Business Media
ISBN 13 : 1475757972
Total Pages : 290 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Matrix Theory by : Fuzhen Zhang

Download or read book Matrix Theory written by Fuzhen Zhang and published by Springer Science & Business Media. This book was released on 2013-03-14 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume concisely presents fundamental ideas, results, and techniques in linear algebra and mainly matrix theory. Each chapter focuses on the results, techniques, and methods that are beautiful, interesting, and representative, followed by carefully selected problems. For many theorems several different proofs are given. The only prerequisites are a decent background in elementary linear algebra and calculus.

Linear Algebra and Matrix Analysis for Statistics

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Publisher : CRC Press
ISBN 13 : 1420095382
Total Pages : 586 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Linear Algebra and Matrix Analysis for Statistics by : Sudipto Banerjee

Download or read book Linear Algebra and Matrix Analysis for Statistics written by Sudipto Banerjee and published by CRC Press. This book was released on 2014-06-06 with total page 586 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Algebra and Matrix Analysis for Statistics offers a gradual exposition to linear algebra without sacrificing the rigor of the subject. It presents both the vector space approach and the canonical forms in matrix theory. The book is as self-contained as possible, assuming no prior knowledge of linear algebra. The authors first address the rudimentary mechanics of linear systems using Gaussian elimination and the resulting decompositions. They introduce Euclidean vector spaces using less abstract concepts and make connections to systems of linear equations wherever possible. After illustrating the importance of the rank of a matrix, they discuss complementary subspaces, oblique projectors, orthogonality, orthogonal projections and projectors, and orthogonal reduction. The text then shows how the theoretical concepts developed are handy in analyzing solutions for linear systems. The authors also explain how determinants are useful for characterizing and deriving properties concerning matrices and linear systems. They then cover eigenvalues, eigenvectors, singular value decomposition, Jordan decomposition (including a proof), quadratic forms, and Kronecker and Hadamard products. The book concludes with accessible treatments of advanced topics, such as linear iterative systems, convergence of matrices, more general vector spaces, linear transformations, and Hilbert spaces.

Introduction to Matrix Analytic Methods in Stochastic Modeling

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Publisher : SIAM
ISBN 13 : 0898714257
Total Pages : 331 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Introduction to Matrix Analytic Methods in Stochastic Modeling by : G. Latouche

Download or read book Introduction to Matrix Analytic Methods in Stochastic Modeling written by G. Latouche and published by SIAM. This book was released on 1999-01-01 with total page 331 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the basic mathematical ideas and algorithms of the matrix analytic theory in a readable, up-to-date, and comprehensive manner.

Matrix Theory

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Publisher : Courier Corporation
ISBN 13 : 0486136388
Total Pages : 319 pages
Book Rating : 4.4/5 (861 download)

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Book Synopsis Matrix Theory by : Joel N. Franklin

Download or read book Matrix Theory written by Joel N. Franklin and published by Courier Corporation. This book was released on 2012-07-31 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematically rigorous introduction covers vector and matrix norms, the condition-number of a matrix, positive and irreducible matrices, much more. Only elementary algebra and calculus required. Includes problem-solving exercises. 1968 edition.

Matrix Analysis for Scientists and Engineers

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Publisher : SIAM
ISBN 13 : 0898715768
Total Pages : 159 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Matrix Analysis for Scientists and Engineers by : Alan J. Laub

Download or read book Matrix Analysis for Scientists and Engineers written by Alan J. Laub and published by SIAM. This book was released on 2005-01-01 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Prerequisites for using this text are knowledge of calculus and some previous exposure to matrices and linear algebra, including, for example, a basic knowledge of determinants, singularity of matrices, eigenvalues and eigenvectors, and positive definite matrices. There are exercises at the end of each chapter."--BOOK JACKET.

Introduction to Applied Linear Algebra

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Publisher : Cambridge University Press
ISBN 13 : 1316518965
Total Pages : 477 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis Introduction to Applied Linear Algebra by : Stephen Boyd

Download or read book Introduction to Applied Linear Algebra written by Stephen Boyd and published by Cambridge University Press. This book was released on 2018-06-07 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

Introduction to Matrix Analysis

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Author :
Publisher : Society for Industrial and Applied Mathematics (SIAM)
ISBN 13 :
Total Pages : 354 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Introduction to Matrix Analysis by : Richard Ernest Bellman

Download or read book Introduction to Matrix Analysis written by Richard Ernest Bellman and published by Society for Industrial and Applied Mathematics (SIAM). This book was released on 1995 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Numerical Matrix Analysis

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Publisher : SIAM
ISBN 13 : 0898716764
Total Pages : 135 pages
Book Rating : 4.8/5 (987 download)

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Book Synopsis Numerical Matrix Analysis by : Ilse C. F. Ipsen

Download or read book Numerical Matrix Analysis written by Ilse C. F. Ipsen and published by SIAM. This book was released on 2009-07-23 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: Matrix analysis presented in the context of numerical computation at a basic level.

Matrix-Based Introduction to Multivariate Data Analysis

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Publisher : Springer
ISBN 13 : 9811023417
Total Pages : 298 pages
Book Rating : 4.8/5 (11 download)

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Book Synopsis Matrix-Based Introduction to Multivariate Data Analysis by : Kohei Adachi

Download or read book Matrix-Based Introduction to Multivariate Data Analysis written by Kohei Adachi and published by Springer. This book was released on 2016-10-11 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book enables readers who may not be familiar with matrices to understand a variety of multivariate analysis procedures in matrix forms. Another feature of the book is that it emphasizes what model underlies a procedure and what objective function is optimized for fitting the model to data. The author believes that the matrix-based learning of such models and objective functions is the fastest way to comprehend multivariate data analysis. The text is arranged so that readers can intuitively capture the purposes for which multivariate analysis procedures are utilized: plain explanations of the purposes with numerical examples precede mathematical descriptions in almost every chapter. This volume is appropriate for undergraduate students who already have studied introductory statistics. Graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis will also find the book useful, as it is based on modern matrix formulations with a special emphasis on singular value decomposition among theorems in matrix algebra. The book begins with an explanation of fundamental matrix operations and the matrix expressions of elementary statistics, followed by the introduction of popular multivariate procedures with advancing levels of matrix algebra chapter by chapter. This organization of the book allows readers without knowledge of matrices to deepen their understanding of multivariate data analysis.

Basics of Matrix Algebra for Statistics with R

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Publisher : CRC Press
ISBN 13 : 1315360055
Total Pages : 159 pages
Book Rating : 4.3/5 (153 download)

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Book Synopsis Basics of Matrix Algebra for Statistics with R by : Nick Fieller

Download or read book Basics of Matrix Algebra for Statistics with R written by Nick Fieller and published by CRC Press. This book was released on 2018-09-03 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Thorough Guide to Elementary Matrix Algebra and Implementation in R Basics of Matrix Algebra for Statistics with R provides a guide to elementary matrix algebra sufficient for undertaking specialized courses, such as multivariate data analysis and linear models. It also covers advanced topics, such as generalized inverses of singular and rectangular matrices and manipulation of partitioned matrices, for those who want to delve deeper into the subject. The book introduces the definition of a matrix and the basic rules of addition, subtraction, multiplication, and inversion. Later topics include determinants, calculation of eigenvectors and eigenvalues, and differentiation of linear and quadratic forms with respect to vectors. The text explores how these concepts arise in statistical techniques, including principal component analysis, canonical correlation analysis, and linear modeling. In addition to the algebraic manipulation of matrices, the book presents numerical examples that illustrate how to perform calculations by hand and using R. Many theoretical and numerical exercises of varying levels of difficulty aid readers in assessing their knowledge of the material. Outline solutions at the back of the book enable readers to verify the techniques required and obtain numerical answers. Avoiding vector spaces and other advanced mathematics, this book shows how to manipulate matrices and perform numerical calculations in R. It prepares readers for higher-level and specialized studies in statistics.