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Exact(8)
In fact, the is the minimum norm point on the.
Then, converges strongly to a minimum norm point on the closed convex set.
Consequently, ({x_{n}}) converges to the minimum norm point of (mathcal{F}).
In fact, the solution of optimization problem (4.4) is named the minimum norm point on the closed convex set.
As special cases, we obtain two iterative methods which converge strongly to the minimum norm point of (operatorname {VI}(C,F) cap operatorname {Fix}(T)).
Remark 3.3 A special form of the optimization problem is to take h ( x ) = ∥ x ∥, which is known as the minimum norm point problem.
Similar(52)
Then { x n } converges strongly to the minimum-norm point x ∗ of ℱ.
Then { x n } converges strongly to the minimum-norm point of F ( T ).
Then ({x_{n}}) converges strongly to the minimum-norm point (x^) of (mathcal{F}).
Then { x n } converges strongly to the minimum-norm point x ∗ of F ( T ) ∩ F ( S ).
Therefore, from the above two cases, we can conclude that { x n } converges strongly to the minimum-norm point of ℱ.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com