ABSTRACT
This chapter aims to familiarize students with some basic theory from linear algebra. It looks at eigenvalues and eigenvectors. MATLAB is a high-level computer programming language. It is important that vector and matrix computations are an intrinsic part of MATLAB. Linear equations can be written in several forms. For each case the solution to the equations has a different interpretation. The rank of a matrix is defined as the number of linearly independent columns, that is, columns that cannot be expressed as a linear combination of the other columns of the matrix. By reducing a matrix to its upper triangular form one's can easily identify how many linearly independent basis vectors there are. Matrices have characteristic directions, called eigenvectors. When an eigenvector is multiplied by the matrix, the result is the eigenvector itself.
