Description

Book Synopsis
Multivariable Mathematics combines linear algebra and multivariable mathematics in a rigorous approach. The material is integrated to emphasize the recurring theme of implicit versus explicit that persists in linear algebra and analysis.

Table of Contents
Preface.

Chapter 1. Vectors and Matrices.

1.1 Vectors in R..

1.2 Dot Product.

1.3 Subspaces of R.

1.4 Linear Transformations and Matrix Algebra.

1.5 Introduction to Determinates and the Cross Product.

Chapter 2. Functions, Limits, and Continuity.

2.1. Scalar- and Vector-Valued Functions.

2.2. A Bit of Topology in R.

2.3. Limits and Continuity.

Chapter 3. The Derivative.

3.1. Partial Derivatives and Directional Derivatives.

3.2. Differentiability.

3.3. Differentiation Rules.

3.4. The Gradient.

3.5. Curves.

3.6. Higher-Order Partial Derivatives.

Chapter 4. Implicit and Explicit Solutions of Linear Systems.

4.1. Gaussian Elimination and the Theory of Linear Systems.

4.2. Elementary Matrices and Calculating Inverse Matrices.

4.3. Linear Independence, Basis, and Dimension.

4.4. The Four Fundamental Subspaces.

4.5. The Nonlinear Case: Introduction to Manifolds.

Chapter 5. Extremum Problems.

5.1. Compactness and the Maximum Value Theorem.

5.2. Maximum/Minimum Problems.

5.3. Quadratic Forms and the Second Derivative Test.

5.4. Lagrange Multipliers.

5.5. Projections, Least Squares, and Inner Product Spaces.

Chapter 6. Solving Nonlinear Problems.

6.1. The Contraction Mapping Principle.

6.2. The Inverse and Implicit Function Theorems.

6.3. Manifolds Revisited.

Chapter 7. Integration.

7.1. Multiple Integrals.

7.2. Iterated Integrals and Fubini’s Theorem.

7.3. Polar, Cylindrical, and Spherical Coordinates.

7.4. Physical Applications.

7.5. Determinants and n-Dimensional Volume.

7.6. Change of Variables Theorem.

Chapter 8. Differential Forms and Integration on Manifolds.

8.1. Motivation.

8.2. Differential Forms.

8.3. Line Integrals and Green’s Theorem.

8.4. Surface Integrals and Flux.

8.5. Stokes’s Theorem.

8.6. Applications to Physics.

8.7. Applications to Topology.

9. Eigenvalues, Eigenvectors, and Applications.

9.1. Linear Transformations and Change of Basis.

9.2. Eigenvalues, Eigenvectors, and Diagonalizability.

9.3. Difference Equations and Ordinary Differential Equations.

9.4. The Spectral Theorem.

Glossary of Notations and Results from Single-Variable Calculus.

For Further Reading.

Answers to Selected Exercises.

Index.

Multivariable Mathematics Linear Algebra

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    A Hardback by Theodore Shifrin

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      View other formats and editions of Multivariable Mathematics Linear Algebra by Theodore Shifrin

      Publisher: John Wiley & Sons Inc
      Publication Date: 9/3/2004 12:00:00 AM
      ISBN13: 9780471631606, 978-0471631606
      ISBN10: 0471631604

      Description

      Book Synopsis
      Multivariable Mathematics combines linear algebra and multivariable mathematics in a rigorous approach. The material is integrated to emphasize the recurring theme of implicit versus explicit that persists in linear algebra and analysis.

      Table of Contents
      Preface.

      Chapter 1. Vectors and Matrices.

      1.1 Vectors in R..

      1.2 Dot Product.

      1.3 Subspaces of R.

      1.4 Linear Transformations and Matrix Algebra.

      1.5 Introduction to Determinates and the Cross Product.

      Chapter 2. Functions, Limits, and Continuity.

      2.1. Scalar- and Vector-Valued Functions.

      2.2. A Bit of Topology in R.

      2.3. Limits and Continuity.

      Chapter 3. The Derivative.

      3.1. Partial Derivatives and Directional Derivatives.

      3.2. Differentiability.

      3.3. Differentiation Rules.

      3.4. The Gradient.

      3.5. Curves.

      3.6. Higher-Order Partial Derivatives.

      Chapter 4. Implicit and Explicit Solutions of Linear Systems.

      4.1. Gaussian Elimination and the Theory of Linear Systems.

      4.2. Elementary Matrices and Calculating Inverse Matrices.

      4.3. Linear Independence, Basis, and Dimension.

      4.4. The Four Fundamental Subspaces.

      4.5. The Nonlinear Case: Introduction to Manifolds.

      Chapter 5. Extremum Problems.

      5.1. Compactness and the Maximum Value Theorem.

      5.2. Maximum/Minimum Problems.

      5.3. Quadratic Forms and the Second Derivative Test.

      5.4. Lagrange Multipliers.

      5.5. Projections, Least Squares, and Inner Product Spaces.

      Chapter 6. Solving Nonlinear Problems.

      6.1. The Contraction Mapping Principle.

      6.2. The Inverse and Implicit Function Theorems.

      6.3. Manifolds Revisited.

      Chapter 7. Integration.

      7.1. Multiple Integrals.

      7.2. Iterated Integrals and Fubini’s Theorem.

      7.3. Polar, Cylindrical, and Spherical Coordinates.

      7.4. Physical Applications.

      7.5. Determinants and n-Dimensional Volume.

      7.6. Change of Variables Theorem.

      Chapter 8. Differential Forms and Integration on Manifolds.

      8.1. Motivation.

      8.2. Differential Forms.

      8.3. Line Integrals and Green’s Theorem.

      8.4. Surface Integrals and Flux.

      8.5. Stokes’s Theorem.

      8.6. Applications to Physics.

      8.7. Applications to Topology.

      9. Eigenvalues, Eigenvectors, and Applications.

      9.1. Linear Transformations and Change of Basis.

      9.2. Eigenvalues, Eigenvectors, and Diagonalizability.

      9.3. Difference Equations and Ordinary Differential Equations.

      9.4. The Spectral Theorem.

      Glossary of Notations and Results from Single-Variable Calculus.

      For Further Reading.

      Answers to Selected Exercises.

      Index.

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