The paper "Geodesic Interpolating Splines" made the following comment on an interpolation problem:
Interpolation problem:
Let $\mathcal{H}$ be a Hilbert space, let $f_1, \dots, f_N \in \mathcal{H}$, and $c_1,\dots,c_N \in \mathbb{R}$ be given.
Find $h \in \mathcal{H}$ such that $\|h\|$ is minimum subject to the constraints $\langle f_i, h \rangle = c_i$ for $i=1,\dots,N$.
Comment:
It is indeed clear that the constraints are not affected if $h$ is replaced by $h + v$ where $v$ is orthogonal to all the $f_i$, so that the solution much be in fact be searched in the linear space spanned by $f_1, \dots, f_N$ and express the unknown $h$ as a linear combination $h = \sum_{i=1}^{N} \alpha_i f_i$.
I understand that the interpolation constraint will remain the same if we replace $h$ by $h + v$. But, how this property implies that the solution should be searched in linear space?
Is it possible to prove their claim with the elementary level knowledge of Hilbert space?
Let $P$ be the orthogonal projection onto the span of $f_i$. If $h$ satisfies the constraints, then so does $P(h)$. But, $||P(h)||\leq||h||$ with equality iff $h$ is in the span of the $f_i$. Thus, for any $h$ that satisfies the constraints outside the span, we can find an element of our Hilbert space with the smaller norm inside the span of the $f_i$.