EDB — 17D

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E14

[17D] Topics:projection.Difficulty:*. Note:This is the well-known ”projection theorem”, which holds for \(A\) convex closed in a Hilbert space; if \(A⊂ ℝ^ n\) then the proof is simpler, and it’s a useful exercise..

Given \(A⊂ ℝ^ n\) closed convex non-empty and \( z∈ ℝ^ n\), show that there is only one minimum point \(x^*\) for the problem

\[ \min _{x∈ A} \| z-x\| ~ . \]
Show that \(x^*\) is the minimum if and only if
\[ ∀ y∈ A , ⟨ z-x^*, y-x^* ⟩≤ 0 ~ ~ . \]
\(x^*\) is called ”the projection of \(z\) on \(A\)”.
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(Note that this last condition is simply saying that the angle must be obtuse.)

Solution 1

[17G]

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  • projection, theorem
  • theorem, projection ---
  • convex function
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