Linear Functions and Matrix Theory

TL;DR: In this paper, the authors introduce the concept of linear algebra in Rn and introduce the matrix product: A Closer Look, the dot product, the cross product, and the Eigenvalues and Eigenvectors.

Abstract: 1 linear Functions.- 1.1 Linear Functions.- 1.2 Local Linearity.- 1.3 Matrices.- 1.4 More Linearity.- 2 Linear Geometry.- 2.1 Linear Geometry in the Plane.- 2.2 Vectors and Lines in the Plane.- 2.3 Linear Geometry in Space.- 2.4 An Introduction to Linear Perspective.- 3 Systems of Linear Equations.- 3.1 Systems of Linear Equations.- 3.2 Gaussian Elimination.- 3.3 Gauss-Jordan Elimination.- 3.4 Matrix Rank and Systems of Linear Equations.- 3.5 The Simplex Algorithm.- 4 Basic Matrix Algebra.- 4.1 The Matrix Product: A Closer Look.- 4.2 Fibonacci Numbers and Difference Equations.- 4.3 The Determinant.- 4.4 Properties and Applications of the Determinant.- 4.5 The LU-Decomposition.- 5 Key Concepts of Linear Algebra in Rn.- 5.1 Linear Combinations and Subspaces.- 5.2 Linear Independence.- 5.3 Basis and Dimension.- 6 More Vector Geometry.- 6.1 The Dot Product.- 6.2 Angles and Projections.- 6.3 The Cross Product.- 7 Eigenvalues and Eigenvectors of Matrices.- 7.1 Eigenvalues and Eigenvectors.- 7.2 Eigenspaces and Diagonalizability.- 7.3 Symmetric Matrices and Probability Matrices.- 8 Matrices as Linear Transformations.- 8.1 Linear Transformations.- 8.2 Using Linear Transformations.- 8.3 Change of Basis.- 9 Orthogonality and Least-Squares Problems.- 9.1 Orthogonality and the Gram-Schmidt Process.- 9.2 Orthogonal Projections.- 9.3 Least-Squares Approximations.- Answers to Odd-Numbered Problems.