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Linear Algebra and Differential Equations, Pearson New International Edition, 1st edition

Published by Pearson (November 1, 2013) © 2014

  • Gary L. Peterson James Madison University
  • James S. Sochacki James Madison University

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Linear Algebra and Differential Equations has been written for a one-semester combined linear algebra and differential equations course, yet it contains enough material for a two-term sequence in linear algebra and differential equations. By introducing matrices, determinants, and vector spaces early in the course, the authors are able to fully develop the connections between linear algebra and differential equations. The book is flexible enough to be easily adapted to fit most syllabi, including separate courses that that cover linear algebra in the first followed by differential equations in the second. Technology is fully integrated where appropriate, and the text offers fresh and relevant applications to motivate student interest.

  • Offers a solid foundation in both linear algebra and differential equations, with an emphasis on finding connections between the two subjects.
  • Contains applications to many areas, including engineering, business, and life sciences.
  • Maple exercises incorporated throughout; support is also offered to users of Mathematica and Matlab in the technology resource manual.



1. Matrices and Determinants.

 

Systems of Linear Equations.

 

 

Matrices and Matrix Operations.

 

 

Inverses of Matrices.

 

 

Special Matrices and Additional Properties of Matrices.

 

 

Determinants.

 

 

Further Properties of Determinants.

 

 

Proofs of Theorems on Determinants.

 



2. Vector Spaces.

 

Vector Spaces.

 

 

Subspaces and Spanning Sets.

 

 

Linear Independence and Bases.

 

 

Dimension; Nullspace, Rowspace, and Column Space.

 

 

Wronskians.

 



3. First Order Ordinary Differential Equations.

 

Introduction to Differential Equations.

 

 

Separable Differential Equations.

 

 

Exact Differential Equations.

 

 

Linear Differential Equations.

 

 

More Techniques for Solving First Order Differential Equations.

 

 

Modeling With Differential Equations.

 

 

Reduction of Order.

 

 

The Theory of First Order Differential Equations.

 

 

Numerical Solutions of Ordinary Differential Equations.

 



4. Linear Differential Equations.

 

The Theory of Higher Order Linear Differential Equations.

 

 

Homogenous Constant Coefficient Linear Differential Equations.

 

 

The Method of Undetermined Coefficients.

 

 

The Method of Variation of Parameters.

 

 

Some Applications of Higher Order Differential Equations.

 



5. Linear Transformations and Eigenvalues and Eigenvectors.

 

Linear Transformations.

 

 

The Algebra of Linear Transformations; Differential Operators and Differential Equations.

 

 

Matrices for Linear Transformations.

 

 

Eigenvectors and Eigenvalues of Matrices.

 

 

Similar Matrices, Diagonalization, and Jordan Canonical Form.

 

 

Eigenvectors and Eigenvalues of Linear Transformations.

 



6 Systems of Differential Equations.

 

The Theory of Systems of Linear Differential Equations.

 

 

Homogenous Systems with Constant Coefficients: The Diagonalizable Case.

 

 

Homogenous Systems with Constant Coefficients: The Nondiagonalizable Case.

 

 

Nonhomogenous Linear Systems.

 

 

Converting Differential Equations to First Order Systems.

 

 

Applications Involving Systems of Linear Differential Equations.

 

 

2x2 Systems of Nonlinear Differential Equations.

 



7. The Laplace Transform.

 

Definition and Properties of the Laplace Transform.

 

 

Solving Constant Coefficient Linear Initial Value Problems with Laplace Transforms.

 

 

Step Functions, Impulse Functions and the Delta Function.

 

 

Convolution Integrals.

 

 

Systems of Linear Differential Equations.

 



8. Power Series Solutions to Linear Differential Equations.

 

Introduction to Power Series Solutions.

 

 

Series Solutions for Second Order Linear Differential Equations.

 

 

Euler Type Equations.

 

 

Series Solutions Near a Regular Singular Point.

 



9. Inner Product Spaces.

 

Inner Product Spaces.

 

 

Orthonormal Bases.

 

 

Schur's Theorem and Symmet

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