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Basic textbook covers theory of matrices and its applications to systems of linear equations and related topics such as determinants eigenvalues and differential equations Numerous exercises both truefalse and multiple choice with each chapter Answer section
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Explore tips, opinions, and features on Linear Algebra and Matrices Topics sold at 55.56 $ ; this product is listed in the Books & Magazines category, produced by , and sold by Abebooks.com.
Linear algebra and matrix theory are fundamental tools for almost every area of mathematics both pure and applied This book combines coverage of core topics with an introduction to some areas in which linear algebra plays a key role for example block designs directed graphs error correcting codes and linear dynamical systems Notable features include a discussion of the Weyr characteristic and Weyr canonical forms and their relationship to the betterknown Jordan canonical form the use of block cyclic matrices and directed graphs to prove Frobeniuss theorem on the structure of the eigenvalues of a nonnegative irreducible matrix and the inclusion of such combinatorial topics as BIBDs Hadamard matrices and strongly regular graphs Also included are McCoys theorem about matrices with property P the BruckRyserChowla theorem on the existence of block designs and an introduction to Markov chains This book is intended for those who are familiar with the linear algebra covered in a typical first course and are interested in learning more advanced results
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Find tips, reviews, and features on Linear Algebra and Matrices Topics sold for 25.02 $ , available in the Books & Magazines category; this product belongs to and is sold by Abebooks.com.
Linear algebra and matrix theory are fundamental tools for almost every area of mathematics both pure and applied This book combines coverage of core topics with an introduction to some areas in which linear algebra plays a key role for example block designs directed graphs error correcting codes and linear dynamical systems Notable features include a discussion of the Weyr characteristic and Weyr canonical forms and their relationship to the betterknown Jordan canonical form the use of block cyclic matrices and directed graphs to prove Frobeniuss theorem on the structure of the eigenvalues of a nonnegative irreducible matrix and the inclusion of such combinatorial topics as BIBDs Hadamard matrices and strongly regular graphs Also included are McCoys theorem about matrices with property P the BruckRyserChowla theorem on the existence of block designs and an introduction to Markov chains This book is intended for those who are familiar with the linear algebra covered in a typical first course and are interested in learning more advanced results
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Explore tips, opinions, and features on Introduction to Applied Linear Algebra sold at 30.37 $ ; this product is listed in the Books & Magazines category, produced by , and sold by Abebooks.com.
This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra Requiring no prior knowledge of the subject it covers the aspects of linear algebra vectors matrices and least squares that are needed for engineering applications discussing examples across data science machine learning and artificial intelligence signal and image processing tomography navigation control and finance The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving realworld problems with lecture slides additional computational exercises in Julia and MATLAB and data sets accompanying the book online Suitable for both onesemester and onequarter courses as well as selfstudy this selfcontained text provides beginning students with the foundation they need to progress to more advanced study
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Discover information, advice, and prices for Introduction to Applied Linear Algebra sold for 55.47 $ , available in the Books & Magazines category; this product is sold by Abebooks.com and made by .
This groundbreaking textbook combines straightforward explanations with a wealth of practical examples to offer an innovative approach to teaching linear algebra Requiring no prior knowledge of the subject it covers the aspects of linear algebra vectors matrices and least squares that are needed for engineering applications discussing examples across data science machine learning and artificial intelligence signal and image processing tomography navigation control and finance The numerous practical exercises throughout allow students to test their understanding and translate their knowledge into solving realworld problems with lecture slides additional computational exercises in Julia and MATLAB and data sets accompanying the book online Suitable for both onesemester and onequarter courses as well as selfstudy this selfcontained text provides beginning students with the foundation they need to progress to more advanced study
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This book covers linear algebra methods for financial engineering applications from a numerical point of view The book contains many such applications as well as pseudocodes numerical examples and questions often asked in interviews for quantitative positions Financial Applications The ArrowDebreu one period market model One period index options arbitrage Covariance and correlation matrix estimation from time series data Ordinary least squares for implied volatility computation Minimum variance portfolios and maximum return portfolios Value at Risk and portfolio VaR Linear Algebra Topics LU and Cholesky decompositions and linear solvers Optimal solvers for tridiagonal symmetric positive matrices Ordinary least squares and linear regression Linear Transformation Property Efficient cubic spline interpolation Multivariate normal random variables The book is written in a similar spirit as the best selling A Primer for the Mathematics of Financial Engineering by the same author and should accordingly be useful to a similarly large audience Prospective students for financial engineering or mathematical finance programs will be able to selfstudy material that will prove very important in their future studies Finance practitioners will find mathematical underpinnings for many methods used in practice furthering the ability to expand upon these methods Academics teaching financial engineering courses will be able to use this book as textbook or as reference book for numerical linear algebra methods with financial applications
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This text covers the fundamental role of linear algebra within both pure and applied mathematics as well as client disciplines such as engineering the physical sciences and economics Linear Algebra examines the interrelationships between theory computation and applications The organization reflects the recent recommendations from the NSFsponsored Study Group in Linear Algebra and the Mathematical Association of America to give more attention to matrix related topics The text integrates contemporary uses of linear algebra with the traditional theory of vector spaces and linear transformations providing math majors with a broader view of linear algebra
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This book covers linear algebra methods for financial engineering applications from a numerical point of view The book contains many such applications as well as pseudocodes numerical examples and questions often asked in interviews for quantitative positions Financial Applications The ArrowDebreu one period market model One period index options arbitrage Covariance and correlation matrix estimation from time series data Ordinary least squares for implied volatility computation Minimum variance portfolios and maximum return portfolios Value at Risk and portfolio VaR Linear Algebra Topics LU and Cholesky decompositions and linear solvers Optimal solvers for tridiagonal symmetric positive matrices Ordinary least squares and linear regression Linear Transformation Property Efficient cubic spline interpolation Multivariate normal random variables The book is written in a similar spirit as the best selling A Primer for the Mathematics of Financial Engineering by the same author and should accordingly be useful to a similarly large audience Prospective students for financial engineering or mathematical finance programs will be able to selfstudy material that will prove very important in their future studies Finance practitioners will find mathematical underpinnings for many methods used in practice furthering the ability to expand upon these methods Academics teaching financial engineering courses will be able to use this book as textbook or as reference book for numerical linear algebra methods with financial applications
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