Analysis And Linear Algebra The Singular Value Decomposition And Applications

Download Analysis And Linear Algebra The Singular Value Decomposition And Applications full books in PDF, epub, and Kindle. Read online Analysis And Linear Algebra The Singular Value Decomposition And Applications ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Analysis and Linear Algebra: The Singular Value Decomposition and Applications

Author : James Bisgard
Publisher : American Mathematical Soc.
ISBN 13 : 1470463326
Total Pages : 217 pages
Book Rating : 4.4/5 (74 download)

DOWNLOAD NOW!

Book Synopsis Analysis and Linear Algebra: The Singular Value Decomposition and Applications by : James Bisgard

Download or read book Analysis and Linear Algebra: The Singular Value Decomposition and Applications written by James Bisgard and published by American Mathematical Soc.. This book was released on 2020-10-19 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an elementary analytically inclined journey to a fundamental result of linear algebra: the Singular Value Decomposition (SVD). SVD is a workhorse in many applications of linear algebra to data science. Four important applications relevant to data science are considered throughout the book: determining the subspace that “best” approximates a given set (dimension reduction of a data set); finding the “best” lower rank approximation of a given matrix (compression and general approximation problems); the Moore-Penrose pseudo-inverse (relevant to solving least squares problems); and the orthogonal Procrustes problem (finding the orthogonal transformation that most closely transforms a given collection to a given configuration), as well as its orientation-preserving version. The point of view throughout is analytic. Readers are assumed to have had a rigorous introduction to sequences and continuity. These are generalized and applied to linear algebraic ideas. Along the way to the SVD, several important results relevant to a wide variety of fields (including random matrices and spectral graph theory) are explored: the Spectral Theorem; minimax characterizations of eigenvalues; and eigenvalue inequalities. By combining analytic and linear algebraic ideas, readers see seemingly disparate areas interacting in beautiful and applicable ways.

Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition

Author : Haruo Yanai
Publisher : Springer Science & Business Media
ISBN 13 : 144199887X
Total Pages : 236 pages
Book Rating : 4.4/5 (419 download)

DOWNLOAD NOW!

Book Synopsis Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition by : Haruo Yanai

Download or read book Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition written by Haruo Yanai and published by Springer Science & Business Media. This book was released on 2011-04-06 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aside from distribution theory, projections and the singular value decomposition (SVD) are the two most important concepts for understanding the basic mechanism of multivariate analysis. The former underlies the least squares estimation in regression analysis, which is essentially a projection of one subspace onto another, and the latter underlies principal component analysis, which seeks to find a subspace that captures the largest variability in the original space. This book is about projections and SVD. A thorough discussion of generalized inverse (g-inverse) matrices is also given because it is closely related to the former. The book provides systematic and in-depth accounts of these concepts from a unified viewpoint of linear transformations finite dimensional vector spaces. More specially, it shows that projection matrices (projectors) and g-inverse matrices can be defined in various ways so that a vector space is decomposed into a direct-sum of (disjoint) subspaces. Projection Matrices, Generalized Inverse Matrices, and Singular Value Decomposition will be useful for researchers, practitioners, and students in applied mathematics, statistics, engineering, behaviormetrics, and other fields.

Data-Driven Science and Engineering

Author : Steven L. Brunton
Publisher : Cambridge University Press
ISBN 13 : 1009098489
Total Pages : 615 pages
Book Rating : 4.0/5 (9 download)

DOWNLOAD NOW!

Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton

Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.

Fundamentals of Matrix Analysis with Applications

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

DOWNLOAD NOW!

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.

Applied Numerical Linear Algebra

Author : James W. Demmel
Publisher : SIAM
ISBN 13 : 0898713897
Total Pages : 426 pages
Book Rating : 4.8/5 (987 download)

DOWNLOAD NOW!

Book Synopsis Applied Numerical Linear Algebra by : James W. Demmel

Download or read book Applied Numerical Linear Algebra written by James W. Demmel and published by SIAM. This book was released on 1997-08-01 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive textbook is designed for first-year graduate students from a variety of engineering and scientific disciplines.

Numerical Linear Algebra and Applications

Author : Biswa Nath Datta
Publisher : SIAM
ISBN 13 : 0898717655
Total Pages : 546 pages
Book Rating : 4.8/5 (987 download)

DOWNLOAD NOW!

Book Synopsis Numerical Linear Algebra and Applications by : Biswa Nath Datta

Download or read book Numerical Linear Algebra and Applications written by Biswa Nath Datta and published by SIAM. This book was released on 2010-01-01 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: Full of features and applications, this acclaimed textbook for upper undergraduate level and graduate level students includes all the major topics of computational linear algebra, including solution of a system of linear equations, least-squares solutions of linear systems, computation of eigenvalues, eigenvectors, and singular value problems. Drawing from numerous disciplines of science and engineering, the author covers a variety of motivating applications. When a physical problem is posed, the scientific and engineering significance of the solution is clearly stated. Each chapter contains a summary of the important concepts developed in that chapter, suggestions for further reading, and numerous exercises, both theoretical and MATLAB and MATCOM based. The author also provides a list of key words for quick reference. The MATLAB toolkit available online, 'MATCOM', contains implementations of the major algorithms in the book and will enable students to study different algorithms for the same problem, comparing efficiency, stability, and accuracy.

Linear Algebra

Author : M. Thamban Nair
Publisher : Springer
ISBN 13 : 9811309264
Total Pages : 341 pages
Book Rating : 4.8/5 (113 download)

DOWNLOAD NOW!

Book Synopsis Linear Algebra by : M. Thamban Nair

Download or read book Linear Algebra written by M. Thamban Nair and published by Springer. This book was released on 2018-07-17 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the fundamental concepts, techniques and results of linear algebra that form the basis of analysis, applied mathematics and algebra. Intended as a text for undergraduate students of mathematics, science and engineering with a knowledge of set theory, it discusses the concepts that are constantly used by scientists and engineers. It also lays the foundation for the language and framework for modern analysis and its applications. Divided into seven chapters, it discusses vector spaces, linear transformations, best approximation in inner product spaces, eigenvalues and eigenvectors, block diagonalisation, triangularisation, Jordan form, singular value decomposition, polar decomposition, and many more topics that are relevant to applications. The topics chosen have become well-established over the years and are still very much in use. The approach is both geometric and algebraic. It avoids distraction from the main theme by deferring the exercises to the end of each section. These exercises aim at reinforcing the learned concepts rather than as exposing readers to the tricks involved in the computation. Problems included at the end of each chapter are relatively advanced and require a deep understanding and assimilation of the topics.

Multidimensional Analysis

Author : George W. Hart
Publisher : Springer Science & Business Media
ISBN 13 : 1461242088
Total Pages : 242 pages
Book Rating : 4.4/5 (612 download)

DOWNLOAD NOW!

Book Synopsis Multidimensional Analysis by : George W. Hart

Download or read book Multidimensional Analysis written by George W. Hart and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with the mathematical properties of dimensioned quantities, such as length, mass, voltage, and viscosity. Beginning with a careful examination of how one expresses the numerical results of a measurement and uses these results in subsequent manipulations, the author rigorously constructs the notion of dimensioned numbers and discusses their algebraic structure. The result is a unification of linear algebra and traditional dimensional analysis that can be extended from the scalars to which the traditional analysis is perforce restricted to multidimensional vectors of the sort frequently encountered in engineering, systems theory, economics, and other applications.

Linear Algebra and Matrix Analysis for Statistics

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

DOWNLOAD NOW!

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.

Practical Linear Algebra for Data Science

Author : Mike Cohen
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (129 download)

DOWNLOAD NOW!

Book Synopsis Practical Linear Algebra for Data Science by : Mike Cohen

Download or read book Practical Linear Algebra for Data Science written by Mike Cohen and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications. This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they're used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you'll be able to understand, implement, and adapt myriad modern analysis methods and algorithms. Ideal for practitioners and students using computer technology and algorithms, this book introduces you to: The interpretations and applications of vectors and matrices Matrix arithmetic (various multiplications and transformations) Independence, rank, and inverses Important decompositions used in applied linear algebra (including LU and QR) Eigendecomposition and singular value decomposition Applications including least-squares model fitting and principal components analysis.

A Practical Approach to Microarray Data Analysis

Author : Daniel P. Berrar
Publisher : Springer Science & Business Media
ISBN 13 : 0306478153
Total Pages : 382 pages
Book Rating : 4.3/5 (64 download)

DOWNLOAD NOW!

Book Synopsis A Practical Approach to Microarray Data Analysis by : Daniel P. Berrar

Download or read book A Practical Approach to Microarray Data Analysis written by Daniel P. Berrar and published by Springer Science & Business Media. This book was released on 2007-05-08 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the past several years, DNA microarray technology has attracted tremendous interest in both the scientific community and in industry. With its ability to simultaneously measure the activity and interactions of thousands of genes, this modern technology promises unprecedented new insights into mechanisms of living systems. Currently, the primary applications of microarrays include gene discovery, disease diagnosis and prognosis, drug discovery (pharmacogenomics), and toxicological research (toxicogenomics). Typical scientific tasks addressed by microarray experiments include the identification of coexpressed genes, discovery of sample or gene groups with similar expression patterns, identification of genes whose expression patterns are highly differentiating with respect to a set of discerned biological entities (e.g., tumor types), and the study of gene activity patterns under various stress conditions (e.g., chemical treatment). More recently, the discovery, modeling, and simulation of regulatory gene networks, and the mapping of expression data to metabolic pathways and chromosome locations have been added to the list of scientific tasks that are being tackled by microarray technology. Each scientific task corresponds to one or more so-called data analysis tasks. Different types of scientific questions require different sets of data analytical techniques. Broadly speaking, there are two classes of elementary data analysis tasks, predictive modeling and pattern-detection. Predictive modeling tasks are concerned with learning a classification or estimation function, whereas pattern-detection methods screen the available data for interesting, previously unknown regularities or relationships.

Numerical Linear Algebra for Applications in Statistics

Author : James E. Gentle
Publisher : Springer Science & Business Media
ISBN 13 : 9780387985428
Total Pages : 244 pages
Book Rating : 4.9/5 (854 download)

DOWNLOAD NOW!

Book Synopsis Numerical Linear Algebra for Applications in Statistics by : James E. Gentle

Download or read book Numerical Linear Algebra for Applications in Statistics written by James E. Gentle and published by Springer Science & Business Media. This book was released on 1998-08-13 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accurate and efficient computer algorithms for factoring matrices, solving linear systems of equations, and extracting eigenvalues and eigenvectors. Regardless of the software system used, the book describes and gives examples of the use of modern computer software for numerical linear algebra. It begins with a discussion of the basics of numerical computations, and then describes the relevant properties of matrix inverses, factorisations, matrix and vector norms, and other topics in linear algebra. The book is essentially self- contained, with the topics addressed constituting the essential material for an introductory course in statistical computing. Numerous exercises allow the text to be used for a first course in statistical computing or as supplementary text for various courses that emphasise computations.

Handbook for Automatic Computation

Author : John H. Wilkinson
Publisher : Springer Science & Business Media
ISBN 13 : 3642869408
Total Pages : 450 pages
Book Rating : 4.6/5 (428 download)

DOWNLOAD NOW!

Book Synopsis Handbook for Automatic Computation by : John H. Wilkinson

Download or read book Handbook for Automatic Computation written by John H. Wilkinson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of the internationally standardized language ALGOL has made it possible to prepare procedures which can be used without modification whenever a computer with an ALGOL translator is available. Volume Ia in this series gave details of the restricted version of ALGOL which is to be employed throughout the Handbook, and volume Ib described its implementation on a computer. Each of the subsequent volumes will be devoted to a presentation of the basic algorithms in some specific areas of numerical analysis. This is the first such volume and it was feIt that the topic Linear Algebra was a natural choice, since the relevant algorithms are perhaps the most widely used in numerical analysis and have the advantage of forming a weil defined dass. The algorithms described here fall into two main categories, associated with the solution of linear systems and the algebraic eigenvalue problem respectively and each set is preceded by an introductory chapter giving a comparative assessment.

Elementary Linear Algebra

Author : Richard O. Hill
Publisher : Academic Press
ISBN 13 : 148326517X
Total Pages : 416 pages
Book Rating : 4.4/5 (832 download)

DOWNLOAD NOW!

Book Synopsis Elementary Linear Algebra by : Richard O. Hill

Download or read book Elementary Linear Algebra written by Richard O. Hill and published by Academic Press. This book was released on 2014-05-10 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Elementary Linear Algebra reviews the elementary foundations of linear algebra in a student-oriented, highly readable way. The many examples and large number and variety of exercises in each section help the student learn and understand the material. The instructor is also given flexibility by allowing the presentation of a traditional introductory linear algebra course with varying emphasis on applications or numerical considerations. In addition, the instructor can tailor coverage of several topics. Comprised of six chapters, this book first discusses Gaussian elimination and the algebra of matrices. Applications are interspersed throughout, and the problem of solving AX = B, where A is square and invertible, is tackled. The reader is then introduced to vector spaces and subspaces, linear independences, and dimension, along with rank, determinants, and the concept of inner product spaces. The final chapter deals with various topics that highlight the interaction between linear algebra and all the other branches of mathematics, including function theory, analysis, and the singular value decomposition and generalized inverses. This monograph will be a useful resource for practitioners, instructors, and students taking elementary linear algebra.

Linear Algebra and Matrix Computations with MATLAB®

Author : Dingyü Xue
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110666995
Total Pages : 301 pages
Book Rating : 4.1/5 (16 download)

DOWNLOAD NOW!

Book Synopsis Linear Algebra and Matrix Computations with MATLAB® by : Dingyü Xue

Download or read book Linear Algebra and Matrix Computations with MATLAB® written by Dingyü Xue and published by Walter de Gruyter GmbH & Co KG. This book was released on 2020-03-23 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Linear Algebra with Applications

Author : William Ford
Publisher : Academic Press
ISBN 13 : 0123947847
Total Pages : 629 pages
Book Rating : 4.1/5 (239 download)

DOWNLOAD NOW!

Book Synopsis Numerical Linear Algebra with Applications by : William Ford

Download or read book Numerical Linear Algebra with Applications written by William Ford and published by Academic Press. This book was released on 2014-09-14 with total page 629 pages. Available in PDF, EPUB and Kindle. Book excerpt: Numerical Linear Algebra with Applications is designed for those who want to gain a practical knowledge of modern computational techniques for the numerical solution of linear algebra problems, using MATLAB as the vehicle for computation. The book contains all the material necessary for a first year graduate or advanced undergraduate course on numerical linear algebra with numerous applications to engineering and science. With a unified presentation of computation, basic algorithm analysis, and numerical methods to compute solutions, this book is ideal for solving real-world problems. The text consists of six introductory chapters that thoroughly provide the required background for those who have not taken a course in applied or theoretical linear algebra. It explains in great detail the algorithms necessary for the accurate computation of the solution to the most frequently occurring problems in numerical linear algebra. In addition to examples from engineering and science applications, proofs of required results are provided without leaving out critical details. The Preface suggests ways in which the book can be used with or without an intensive study of proofs. This book will be a useful reference for graduate or advanced undergraduate students in engineering, science, and mathematics. It will also appeal to professionals in engineering and science, such as practicing engineers who want to see how numerical linear algebra problems can be solved using a programming language such as MATLAB, MAPLE, or Mathematica. Six introductory chapters that thoroughly provide the required background for those who have not taken a course in applied or theoretical linear algebra Detailed explanations and examples A through discussion of the algorithms necessary for the accurate computation of the solution to the most frequently occurring problems in numerical linear algebra Examples from engineering and science applications

Linear Algebra for Pattern Processing

Author : Kenichi Kanatani
Publisher : Morgan & Claypool Publishers
ISBN 13 : 1636391087
Total Pages : 157 pages
Book Rating : 4.6/5 (363 download)

DOWNLOAD NOW!

Book Synopsis Linear Algebra for Pattern Processing by : Kenichi Kanatani

Download or read book Linear Algebra for Pattern Processing written by Kenichi Kanatani and published by Morgan & Claypool Publishers. This book was released on 2021-04-30 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear algebra is one of the most basic foundations of a wide range of scientific domains, and most textbooks of linear algebra are written by mathematicians. However, this book is specifically intended to students and researchers of pattern information processing, analyzing signals such as images and exploring computer vision and computer graphics applications. The author himself is a researcher of this domain. Such pattern information processing deals with a large amount of data, which are represented by high-dimensional vectors and matrices. There, the role of linear algebra is not merely numerical computation of large-scale vectors and matrices. In fact, data processing is usually accompanied with "geometric interpretation." For example, we can think of one data set being "orthogonal" to another and define a "distance" between them or invoke geometric relationships such as "projecting" some data onto some space. Such geometric concepts not only help us mentally visualize abstract high-dimensional spaces in intuitive terms but also lead us to find what kind of processing is appropriate for what kind of goals. First, we take up the concept of "projection" of linear spaces and describe "spectral decomposition," "singular value decomposition," and "pseudoinverse" in terms of projection. As their applications, we discuss least-squares solutions of simultaneous linear equations and covariance matrices of probability distributions of vector random variables that are not necessarily positive definite. We also discuss fitting subspaces to point data and factorizing matrices in high dimensions in relation to motion image analysis. Finally, we introduce a computer vision application of reconstructing the 3D location of a point from three camera views to illustrate the role of linear algebra in dealing with data with noise. This book is expected to help students and researchers of pattern information processing deepen the geometric understanding of linear algebra.