Definition.
R
R
is a
(homogeneous) linear transformation (h.l.t.) if
(i)
v
w
v
w
, for any
v
w (``additivity''), and
(ii)
v
v
, for any vector
v
and scalar
(``homogeneity'').
Example. Let be an
matrix,
and let
be defined by
x
x
(where
x
is any row vector). Then
is a homogeneous linear
transformation, by the rules for matrices.
Observations. If is a homogeneous linear
transformation, then
(a)
0
0 (the origin goes to the origin),
(b)
v
w
v
w
(
is
compatible with linear combinations).
Outline of proof.
For any , let
be the matrix whose
-th row is
e
; then
x
is the same as
x
for
x
one of the
e
and so for any
x,
since every vector
x in
R
is a linear combination
of standard basis vectors and
preserves linear combinations.
Thus
.
Remarks
(1) The word ``homogeneous'' really refers to the property (ii). Homogeneous linear transformations leave the origin fixed. We emphasize the word because we'll also be considering ``affine'' transformations, which are a generalization of linear transformations in which the origin can be moved. Because these still take lines to lines, some texts also call affine transformations ``linear''.
(2) If we're thinking about homogeneous linear transformations
abstractly we'll use just the letter ; if we have
in
mind we'll use
. By the Theorem these two points of
view are equivalent. Later on we'll use
for other kinds
of transformations as well.
(3) The definition of
x
as
x
assumes that
the
-tuple
x is represented as a row vector; this is a
common assumption in computer graphics packages. If we use column
vectors, it would be
x. Notes in this course generally assume
row vectors.
(4) In projective geometry, it is shown
that any one-to-one transformation of
R onto itself taking
lines to lines and the origin to the origin must be a
homogeneous linear transformation. (This is a deep fact.)