5: Linear Transformations
( \newcommand{\kernel}{\mathrm{null}\,}\)
- 5.1: Linear Transformations
- In this section we will consider how matrix multiplication transforms vectors while preserving vector addition and scalar multiplication. Such transformations are called linear transformations.
- 5.2: The Matrix of a Linear Transformation I
- In the previous section we saw that multiplication by a matrix is a linear transformation. It turns out that it is always the case that if T is any linear transformation which maps Rn to Rm, then it corresponds to multiplication by a matrix.
- 5.3: Properties of Linear Transformations
- Let T:Rn↦Rm be a linear transformation. Then there are some important properties of T which will be examined in this section.
- 5.4: Special Linear Transformations in Two and Three Dimensions
- In this section, we will examine some special examples of linear transformations in R2 including rotations, reflections., and projections.
- 5.5: One-to-One and Onto Transformations
- This section is devoted to studying two important characterizations of linear transformations, called One to One and Onto.
- 5.6: Isomorphisms
- In this section we will consider linear transformations that are one to one and onto. Such linear transformations are called isomorphisms.
- 5.7: The Kernel and Image of A Linear Map
- In this section we will consider two important subspaces associated with a linear transformation: its kernel and its image.
- 5.8: The Matrix of a Linear Transformation II
- In this section we learn how to represent a linear transformation with respect to different bases.
- 5.9: The General Solution of a Linear System
- In this section we see how to use linear transformations to solve linear systems of equations.
Thumbnail: A linear combination of one basis set of vectors (purple) obtains new vectors (red). If they are linearly independent, these form a new basis set. The linear combinations relating the first set to the other extend to a linear transformation, called the change of basis. (CC BY-SA; Maschen via Wikipedia)