CONTENTS

Preface

1 Basics of Linear Algebra

1.1 Notation and Terminology

1.2 Vector and Matrix Norms

1.3 Dot Product and Orthogonality

1.4 Special Matrices

1.4.1 Diagonal and triangular matrices

1.4.2 Hessenberg matrices

1.4.3 Nonsingular and inverse matrices

1.4.4 Symmetric and positive definite matrices

1.4.5 Matrix exponential

1.4.6 Permutation matrices

1.4.7 Orthogonal matrices

1.5 Vector Spaces

1.6 Linear Independence and Basis

1.7 Orthogonalization and Direct Sums

1.8 Column Space, Row Space, and Null Space

1.8.1 Linear transformations

1.9 Orthogonal Projections

1.10 Eigenvalues and Eigenvectors

1.11 Similarity

1.12 Bezier Curves and Postscript Fonts

1.12.1 Properties of Bezier curves

1.12.2 Composite Bezier curves

1.13 Final Remarks and Further Reading

Exercises

2 Ranking Web Pages

2.1 The Power Method

2.2 Stochastic, Irreducible, and Primitive Matrices

2.3 Google's PageRank Algorithm

2.3.1 The personalization vector

2.3.2 Speed of convergence and sparsity

2.3.3 Power method and reordering

2.4 Alternatives to the Power Method

2.4.1 Linear system formulation

2.4.2 Iterative aggregation/disaggregation (IAD)

2.4.3 IAD and linear systems

2.5 Final Remarks and Further Reading

Exercises

3 Matrix Factorizations

3.1 LU Factorization

3.1.1 The complex case

3.1.2 Solving several systems

3.1.3 The PA = LU factorization

3.2 QR Factorization

3.2.1 QR and Gram–Schmidt

3.2.2 The complex case

3.2.3 QR and similarity

3.2.4 The QR algorithm

3.2.5 QR and LU

3.3 Singular Value Decomposition (SVD)

3.3.1 The complex case

3.3.2 Low–rank approximations

3.3.3 SVD and spectral norm

3.4 Schur Factorization

3.4.1 The complex case

3.4.2 Schur factorization and invariant subspaces

3.4.3 Exchanging eigenblocks

3.4.4 Block diagonalization

3.5 Information Retrieval

3.5.1 Query matching

3.5.2 Low-rank query matching

3.5.3 Term–term comparison

3.6 Partition of Simple Substitution Cryptograms

3.6.1 Rank-1 approximation

3.6.2 Rank-2 approximation

3.7 Final Remarks and Further Reading

Exercises

4 Least Squares

4.1 Projections and Normal Equations

4.2 Least Squares and QR Factorization

4.3 Lagrange Multipliers

4.4 Final Remarks and Further Reading

Exercises

5 Image Compression

5.1 Compressing with Discrete Cosine Transform

5.1.1 1 -D discrete cosine transform

5.1.2 2-D discrete cosine transform

5.1.3 Image compression and the human visual system

5.1.4 Basis functions and images

5.1.5 Low-pass filtering

5.1.6 Quantization

5.1.7 Compression of color images

5.2 Huffman Coding

5.2.1 Huffman coding and JPEG

5.3 Compression with SVD

5.3.1 Compressing grayscale images

5.3.2 Compressing color images

5.4 Final Remarks and Further Reading

Exercises

6 Ordinary Differential Equations

6.1 One-Dimensional Differential Equations

6.1.1 Existence and uniqueness

6.1.2 A simple population model

6.1.3 Emigration

6.1.4 Time-varying emigration

6.1.5 Competition

6.1.6 Spring systems

6.1.7 Undamped equations

6.1.8 Damped equations

6.1.9 RLC circuits

6.2 Linear Systems of Differential Equations

6.3 Solutions via Eigenvalues and Eigenvectors

6.3.1 Chains of generalized eigenvectors

6.4 Fundamental Matrix Solution

6.4.1 Nonhomogeneous systems

6.5 Final Remarks and Further Reading

Exercises

7 Dynamical Systems

7.1 Linear Dynamical Systems

7.1.1 Dynamics in two dimensions

7.1.2 Trace-determinant analysis

7.1.3 Stable, unstable, and center subspaces

7.2 Nonlinear Dynamical Systems

7.2.1 Linearization around an equilibrium point

7.2.2 Linearization around a periodic orbit

7.2.3 Connecting orbits

7.2.4 Chaos

7.2.5 Bifurcations

7.3 Predator–prey Models with Harvesting

7.3.1 Boundedness of solutions

7.3.2 Equilibrium point analysis

7.3.3 Bifurcations

7.3.4 Connecting orbits

7.3.5 Other models

7.4 Final Remarks and Further Reading

Exercises

8 Mathematical Models

8.1 Optimization of a Waste Management System

8.1.1 Background

8.1.2 Description of the system

8.1.3 Development of the mathematical model

8.1.4 Building the objective function

8.1.5 Building the constraints

8.1.6 Numerical experiments

8.2 Grouping Problem in Networks

8.2.1 Background

8.2.2 The N-median approach

8.2.3 The probabilistic approach

8.2.4 Numerical experiments

8.3 American Cutaneous Leishmaniasis

8.3.1 Background

8.3.2 Development of the mathematical model

8.3.3 Equilibria and periodic orbits

8.3.4 Stability properties

8.3.5 Numerical computations

8.4 Variable Population Interactions

8.4.1 Model formulation

8.4.2 Local stability of equilibria

8.4.3 Bifurcations

References

Index

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