Hilbert projection theorem
In mathematics, the Hilbert projection theorem is a famous result of convex analysis that says that for every point in a Hilbert space and every closed convex , there exists a unique point for which is minimized over .
This is, in particular, true for any closed subspace of . In that case, a necessary and sufficient condition for is that the vector be orthogonal to .
- Let us show the existence of y:
Let δ be the distance between x and C, (yn) a sequence in C such that the distance squared between x and yn is below or equal to δ2 + 1/n. Let n and m be two integers, then the following equalities are true:
We have therefore:
By giving an upper bound to the first two terms of the equality and by noticing that the middle of yn and ym belong to C and has therefore a distance greater than or equal to δ from x, one gets :
The last inequality proves that (yn) is a Cauchy sequence. Since C is complete, the sequence is therefore convergent to a point y in C, whose distance from x is minimal.
- Let us show the uniqueness of y :
Let y1 and y2 be two minimizer. Then:
Since belongs to C, we have and therefore
Hence , which proves unicity.
- Let us show the equivalent condition on y when C = M is a closed subspace.
The condition is sufficient: Let such that for all . which proves that is a minimizer.
The condition is necessary: Let be the minimizer. Let and .
is always non-negative. Therefore,
- Walter Rudin, Real and Complex Analysis. Third Edition, 1987.