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# Principles of linear algebra with Mathematica

Author: Kenneth Shiskowski; Karl Frinkle Hoboken, N.J. : Wiley, ©2011. Pure and applied mathematics (John Wiley & Sons : Unnumbered) Print book : EnglishView all editions and formats "Principles of Linear Algebra with Mathematica uniquely addresses the quickly growing intersection between subject theory and numerical computation. Computer algebra systems such as Mathematica are becoming ever more powerful, useful, user friendly and readily available to the average student and professional, but thre are few books which currently cross this gap between linear algebra and Mathematica. This book introduces algebra topics which can only be taught with the help of computer algebra systems, and the authors include all of the commands required to solve complex and computationally challenging linear algebra problems using Mathematica. The book begins with an introduction to the commands and programming guidelines for working with Mathematica®. Next, the authors explore linear systems of equations and matrices, applications of linear systems and matrices, determinants, inverses, and Cramer's rule. Basic linear algebra topics, such as vectors, dot product, cross product, vector projection, are explored as well as the more advanced topics of rotations in space, rolling a circle along a curve, and the TNB Frame. Subsequent chapters feature coverage of linear programming, linear transformations from Rn to Rm, the geometry of linear and affine transformations, and least squares fits and pseudoinverses. Although computational in nature, the material is not presented in a simply theory-proof-problem format. Instead, all topics are explored in a reader-friendly and insightful way. The Mathematica® software is fully utilized to highlight the visual nature of the topic, as the book is complete with numerous graphics in two and three dimensions, animations, symbolic manipulations, numerical computations, and programming. Exercises are supplied in most chapters, and a related Web site houses Mathematica® code so readers can work through the provided examples"--  Read more... (not yet rated) 0 with reviews - Be the first.

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Material Type: Internet resource Book, Internet Resource Kenneth Shiskowski; Karl Frinkle Find more information about: Kenneth Shiskowski Karl Frinkle 9780470637951 0470637951 701014977 Machine generated contents note: Preface. Conventions and Notations.1. An Introduction to Mathematica.1.1 The Very Basics.1.2 Basic Arithmetic.1.3 Lists and Matrices.1.4 Expressions Versus Functions.1.5 Plotting and Animations.1.6 Solving Systems of Equations.1.7 Basic Programming.2. Linear Systems of Equations and Matrices.2.1 Linear Systems of Equations.2.2 Augmented Matrix of a Linear System and Row Operations.2.3 Some Matrix Arithmetic.3. Gauss-Jordan Elimination and Reduced Row Echelon Form.3.1 Gauss-Jordan Elimination and rref.3.2 Elementary Matrices.3.3 Sensitivity of Solutions to Error in the Linear System.4. Applications of Linear Systems and Matrices.4.1 Applications of Linear Systems to Geometry.4.2 Applications of Linear Systems to Curve Fitting.4.3 Applications of Linear Systems to Economics.4.4 Applications of Matrix Multiplication to Geometry.4.5 An Application of Matrix Multiplication to Economics.5. Determinants, Inverses, and Cramer' Rule.5.1 Determinants and Inverses from the Adjoint Formula.5.2 Determinants by Expanding Along Any Row or Column.5.3 Determinants Found by Triangularizing Matrices.5.4 LU Factorization.5.5 Inverses from rref.5.6 Cramer's Rule.6. Basic Linear Algebra Topics.6.1 Vectors.6.2 Dot Product.6.3 Cross Product.6.4 A Vector Projection.7. A Few Advanced Linear Algebra Topics.7.1 Rotations in Space.7.2 "Rolling" a Circle Along a Curve.7.3 The TNB Frame.8. Independence, Basis, and Dimension for Subspaces of Rn.8.1 Subspaces of Rn.8.2 Independent and Dependent Sets of Vectors in Rn.8.3 Basis and Dimension for Subspaces of Rn.8.4 Vector Projection onto a subspace of Rn.8.5 The Gram-Schmidt Orthonormalization Process.9. Linear Maps from Rn to Rm.9.1 Basics About Linear Maps.9.2 The Kernel and Image Subspaces of a Linear Map.9.3 Composites of Two Linear Maps and Inverses.9.4 Change of Bases for the Matrix Representation of a Linear Map.10. The Geometry of Linear and Affine Maps.10.1 The Effect of a Linear Map on Area and Arclength in Two Dimensions.10.2 The Decomposition of Linear Maps into Rotations, Reflections, and Rescalings in R2.10.3 The Effect of Linear Maps on Volume, Area, and Arclength in R3. 10.4 Rotations, Reflections, and Rescalings in Three Dimensions.10.5 Affine Maps.11. Least-Squares Fits and Pseudoinverses.11.1 Pseudoinverse to a Nonsquare Matrix and Almost Solving an Overdetermined Linear System.11.2 Fits and Pseudoinverses.11.3 Least-Squares Fits and Pseudoinverses.12. Eigenvalues and Eigenvectors.12.1 What Are Eigenvalues and Eigenvectors, and Why Do We Need Them?12.2 Summary of Definitions and Methods for Computing Eigenvalues and Eigenvectors as well as the Exponential of a Matrix.12.3 Applications of the Diagonalizability of Square Matrices.12.4 Solving a Square First-Order Linear System if Differential Equations.12.5 Basic Facts About Eigenvalues, Eigenvectors, and Diagonalizability.12.6 The Geometry of the Ellipse Using Eigenvalues and Eigenvectors.12.7 A Mathematica EigenFunction. Suggested Reading. Indices. Keyword Index. Index of Mathematica Commands. xiv, 598 pages : illustrations ; 25 cm. An introduction to mathematica -- Linear systems of equations and matrices -- Gauss-Jordan elimination and reduced row echelon form -- Applications of linear systems and matrices -- Determinants, inverses, and Cramer's rule -- Basic vector algebra topics -- A few advanced linear algebra topics -- Independence, basis, and dimension for subspaces of Rn -- Linear maps from Rn to Rm -- The geometry of linear and affine maps -- Least-squares fits and pseudoinverses -- Eigenvalues and eigenvectors. Pure and applied mathematics (John Wiley & Sons : Unnumbered) Kenneth Shiskowski, Karl Frinkle.

### Abstract:

* All Mathematica(R) commands used to solve and explain the book's theories and examples are provided both in the book and on a related Web site, allowing readers to modify these commands on their  Read more...

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"An accessible introduction to the theoretical and computational aspects of linear algebra using Maple(TM)." (TMCnet.com, 16 April 2011)

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