Recall what an inner product space is. Now, define . Define

Given an inner product on a vector space, we can always define a norm on the vector space by

On ,

On , we can also define a sup-norm

Theorem 1.

is a complete normed linear space.

Proof
We have to show that every Cauchy sequence in converges (in , of course). Suppose is a Cauchy sequence in . Then, given , such that . So, satisfies the Cauchy criterion for uniform convergence. Thus, , where is continuous.

Note that and , where the latter uses the norm induced by the inner product, are different spaces. The first one is complete, and the second one is not. As a counter example, consider the sequence of functions in . They converge to a function which is at and everywhere else - certainly not in . However, the sequence of functions is a Cauchy sequence with respect to : For every , such that . While we are at it, also note that is not a Cauchy sequence in .


Refer Treil (2014) chapter 5 for parallelogram identity, polarization identity, and the relation between norms and inner products. Basically, every inner product space can be made into a NLS by the standard definition (). However, an inner product can be defined on an NLS iff the norm satisfies the parallelogram law.


References

Treil, S. (2014). Linear Algebra Done Wrong.