Due by Fri, 12 Jan 2018
In this exercise, we explore further the relation between norms and inner-products. Let $V$ be a vector space over $\mathbb{R}$.
We shall see that:
$~$
We take these properties to be the definition of a norm, i.e., a norm is a function $\Vert\cdot\Vert: V \to \mathbb{R}$ that satisfies the properties (1) - (3).
Let $\langle\cdot, \cdot \rangle$ be an inner-product on $V$ and define $\Vert x \Vert = \sqrt{\langle x, x\rangle}$ for $x \in V$. Show that for $x, y \in V$,
This is called the parallelogram law.
Let $V = \mathbb{R^2}$ and define $\Vert (x, y)\Vert = \vert x \vert + \vert y \vert$. Show that $\Vert\cdot\Vert$ satisfies the properties (1) - (3) of problem 1 (i.e., it is a norm), but not the parallelogram law (and is thus not obtained from an inner product).
Suppose a norm $\Vert\cdot\Vert$ on a vector space $V$ is of the form $\Vert x \Vert = \sqrt{\langle x, x\rangle}$ for an inner product $\langle\cdot, \cdot \rangle$, then show that the inner product is given by
This is called the polarization identity.
Remark: In fact, if a norm satisfies the parallelogram law, then the polarization identity gives an inner product (this is harder to prove than the above statements).