Let V Be the Vector Space of Continuous Fzunctions F R R Show That the Product Defined Below
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Next: Linear Independence Up: Calculus Revisited Previous: Calculus Revisited
Vector Spaces
Recall the theorem about sums and multiples of continuous functions: If and
are continuous on an interval
and
is any real number, then
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and | ||
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This theorem says that the set of functions continuous on
![$ [a,b]$](https://www.math.tamu.edu/~dallen/DistanceEd/Math640/chapter3/img1406.gif)
![$ C[a,b]$](https://www.math.tamu.edu/~dallen/DistanceEd/Math640/chapter3/img1409.gif)
![$ [a,b]$](https://www.math.tamu.edu/~dallen/DistanceEd/Math640/chapter3/img1406.gif)
![$ C[a,b]$](https://www.math.tamu.edu/~dallen/DistanceEd/Math640/chapter3/img1409.gif)
are easily checked. The zero vector is the constant function (it is continuous) which is identically zero on
![$ [a,b]$](https://www.math.tamu.edu/~dallen/DistanceEd/Math640/chapter3/img1406.gif)
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![$ C[a,b]$](https://www.math.tamu.edu/~dallen/DistanceEd/Math640/chapter3/img1409.gif)
Differentiable functions are another important set of functions in calculus. If we define as the set of functions
defined on
with
(that is,
is continuous) and give
the same operations as
, then
is a subspace of
. To see this, we need only check closure. Since a theorem from calculus tells us that the sum and constant multiples of differentiable functions are differentiable, we have the necessary closure. So
is a vector space in its own right as well as a subspace of
.
Example 1 Give an example of a function in which is not in
. This shows that
is a proper subspace of
.
Solution A continuous function which is not differentiable will be sufficient. The function is continuous on
but fails to have a derivative at
.
Several functions from calculus are differentiable an infinite number of times. For example, ,
,
, and all polynomials are infinitely differentiable over all
. Thus we can define vector spaces
Example 2 Give a example of a function which is in but is not in
.
Solution Let . Then
and
. Although
is continuous on
is not, because
is undefined.
Examples 1 and 2 illustrate the subspace relationship
The vector space differs from the vector spaces we have been studying in that
is not finite-dimensional. To see this, suppose that
. Then a finite basis
of continuous functions in
would exist, and any set of
functions would have to be linearly dependent. However,
is a set of
functions in
which are linearly independent. So it is impossible to have
for any
. Since polynomials are infinitely differentiable, the same argument shows that
is not finite-dimensional for any
.
Although is not finite-dimensional, there are important finite-dimensional subspaces of
.
Example 3 Show that the set of all solutions to the equation3.3
is a one-dimensional subspace of
Solution We recall that the functions3.4 satisfying are
, where
is arbitrary. That is,
. To show that
is a subspace of
, we first note that since
is a continuous function,
. Now closure of
under the operations must be shown. Since
and
, we have the closure, so
is a subspace of
. A basis for
is
. Thus
.
Example 4 Show that the set of all solutions to the equation
is a two-dimensional subspace of
.
Solution The solutions of the equation are of the form . Showing that
is a subspace is done in the same way as Example 3. A basis for
is
. That
spans
is easy. For the linear independence consider
. The equation must hold for all
. Substitute
to find
. Substitute
to obtain
.
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Next: Linear Independence Up: Calculus Revisited Previous: Calculus Revisited
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