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Therefore, if one takes to be the identity operator, then the regularized solution of the corresponding regularized VIP (2.1) converges in norm to the minimal norm point of the solution set.
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We prove that the sequence {x n } generated by (1.5) and (1.6) converge strongly to the element of minimal norm fixed point of nonexpansive mappings.
This technique uses (strict) contractions to regularize a nonexpansive mapping for the purpose of selecting a particular fixed point of the nonexpansive mapping, for instance, the fixed point of minimal norm, or of a solution to another variational inequality.
So, it admits a point of minimal norm.
This is equivalent to saying that there is a point with minimal norm in the translated convex set D = C − x.
Using Tychonov regularization, we obtain a net of solutions for some minimization problem approximating such minimal norm solutions.
The proof consists in showing that every minimizing sequence (dn) ⊂ D is Cauchy (using the parallelogram identity) hence converges (using completeness) to a point in D that has minimal norm.
Then the sequence {x n } generated by the algorithm (1.6) strongly converges to a fixed point of T which is of minimal norm.
We ask whether, for such a norm, there is some map in H1/2(S1;S1) of prescribed topological degree equal to 1 and minimal norm.
Then, using Tychonov regularization, we obtain the minimal norm solution by a net of solution for some minimization problem.
In this section, we define the concept of the minimal norm solution of SEP (1.1).
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