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Example Question #51 : Linear Mapping
is the set of all two-by-one matrices - that is, the set of all column matrices with two entries.
Let . Define a linear mapping
as follows:
.
True or false: is one-to-one and onto.
True
False; is neither one-to-one nor onto
False; is one-to-one but not onto
False; is onto but not one-to-one
False; is neither one-to-one nor onto
The domain and the codomain of are identical, so
is one to one if and only if it is onto.
A necessary and sufficient condition for to be one-to-one is that the kernel of
be
. In
, the zero element is
, and this condition states that if
, then
Thus, we can prove that is not one-to-one - and not onto - by finding a nonzero column matrix
such that
.
Set . Then
There is at least one nonzero column matrix in the kernel of , so
is not one-to-one or onto.
Example Question #531 : Operations And Properties
is the set of all polynomials of finite degree in
.
Define a linear mapping as follows:
.
True or false: is a one-to-one and onto linear mapping.
False: is neither one-to-one nor onto.
True
False: is one-to-one but not onto.
False: is onto but not one-to-one.
False: is onto but not one-to-one.
The domain and the codomain are both of infinite dimension, so it is possible for be one-to-one, onto, both, or neither.
is one-to-one if and only if
implies
.
Let and
Then
and
.
Since
, but
,
is not one-to-one.
Now let , where finitely many
are nonzero.If
,
then
is therefore onto.
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