The change of basis is a technique that allows us to express vector coordinates with respect to a "new basis" that is different from the "old basis" originally employed to compute coordinates.
Suppose that a finite-dimensional
vector space
possesses a basis
.
Then, any vector
can be written as a linear combination of the
basis:
where
the scalar coefficients
are uniquely determined.
Remember that the
vector
is
called the coordinate vector
of
with respect to the basis
.
Example
Let
be a vector space and
a basis for
.
Consider the
vector
Its
coordinate vector
is
Suppose that we have a second basis
.
By the dimension
theorem,
and
have the same number
of vectors.
But what happens to coordinates when we switch from using
as a basis to using
?
In particular, how do we transform a coordinate vector
into a vector
of coordinates with respect to the new basis?
The answer is provided by the following proposition.
Proposition
Let
be a vector space. Let
and
be two bases for
.
Then, there exists a
matrix, denoted by
and called change-of-basis matrix, such that, for any
,
where
and
denote the coordinate vectors of
with respect to
and
respectively.
Let
be
the representation of
in terms of
.
By the rules on the addition and
scalar multiplication of coordinate vectors, we have
that
where
are the
coordinate vectors of the elements of
with respect to
.
Adjoin these
vectors so as to form a
matrix
Since
we
can write equation (1)
as
because
the product
is equal to a linear combination of the columns of
,
with coefficients taken from
(see the lecture on
matrix
products and linear combinations). Note that
does not depend on the particular choice of
,
as it depends only on the two bases
and
.
The main take-away from the previous proof is that the columns of the
change-of-basis matrix
are the coordinates of the vectors of the original basis
with respect to the new basis
:
As demonstrated by the next proposition, the change of basis matrix is invertible.
Proposition
Let
be a vector space. Let
and
be two bases for
.
Then, the change-of-basis matrix
is invertible and its inverse
equals
,
that
is,
For any
,
we have
that
and
By
combining these two equations, we
obtain
This
can be true for every
only if
where
is the
identity matrix. The latter
result implies that
is the inverse of
.
Let us make an example.
Consider the space
of all
vectors and the two bases:
with
with
We
have
Thus, the coordinate vectors of the elements of
with respect to
are
Therefore, when we switch from
to
,
the change-of-basis matrix
is
For example, take the
vector
Sincethe
coordinates of
with respect to
are
Its coordinates with respect to
can be easily computed thanks to the change-of-basis
matrix:
We can easily check that this is
correct:
Remember that a linear operator on a vector space
is a function
such
that
for
any two vectors
and any two scalars
and
.
Given a basis
for
,
the matrix of the linear
operator with respect to
is the square
matrix
such
that
for
any vector
(see also the lecture on the
matrix of a linear map).
In other words, if you multiply the matrix of the operator by the coordinate
vector of
,
then you obtain the coordinate vector of
.
What happens to the matrix of the operator when we switch to a new basis? The next proposition provides an answer to this question.
Proposition
Let
be a linear space. Let
and
be two bases for
.
Let
be a linear operator. Denote by
and
the matrices of the linear operator with respect to
and
respectively. Then,
or,
equivalently,
where
and
are the change-of-basis matrices that allow us to switch from
to
and vice versa.
Let
.
We can use the change-of-basis matrix
to transform the
coordinates
and
Therefore,
the matrix representation of the
operator
can
be written
as
or
Thus,
the
matrix
is
the matrix of
with respect to
(which is unique). In other
words,
Since
we
can also
write
Thus, the change-of-basis matrices allow us to easily switch from the matrix of the linear operator with respect to the old basis to the matrix with respect to the new basis.
Below you can find some exercises with explained solutions.
Let us consider the space
introduced in the example above with the two bases
and
.
In that example, we have shown that the change-of-basis matrix
is
Moreover,
Let
be the linear operator such
that
Find the matrix
and then use the change-of-basis formulae to derive
from
.
The matrix of the linear operator with
respect to the basis
is
The
change-of-basis formula
gives
Please cite as:
Taboga, Marco (2021). "Change of basis", Lectures on matrix algebra. https://www.statlect.com/matrix-algebra/change-of-basis.
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