Let be a finite dimensional vector space over the field , with .
We also define the ordered basis for to be .
Consider a subspace of the vector space . Naturally, we have .
This is because for any , we have , which can then be expressed as a linear combination of the basis vectors in . Hence, we don’t require more than linearly independent vectors to represent any vector in .
Now what if is a proper subspace, ?
At first glance, it might seem like we still have , but in fact we have a strict inequality .
To see this, we let . Let the ordered basis of be .
As is a proper subspace, we can choose an element such that . Intuitively, the vectors are linearly independent as cannot be expressed as a linear combination of the vectors in . To see this mathematically, consider the following linear combination of the basis vectors in and with scalars taken from the field :
For this to be satisfied, we must have all . To prove this, we first assume that . We can now multiply both sides by (Which is possible because is also an element of the field, for ).
The above equation means that either can be expressed as a linear combination of the basis vectors of (If some of the ), or . Both of these would mean that , which is not the case as we have specifically chosen . Hence this means that cannot be non-zero.
As is the basis for , they are linearly independent, and we must have in the above equation.
So for the linear combination of the basis vectors in and to be equal to , we must have every , implying that the basis vectors in along with are linearly independent.
We now have a set of linearly independent vectors within . Hence which means that , giving us the strict inequality between the dimensions of both vector spaces:
See Also
- Change of basis
- Injective linear transformations
- Implicit Euler integration using Newton-Raphson
- ZMP: Generating Bipedal Walking Trajectories
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