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For disabled people this referent has historically and pervasively been constructed in relation to approximating the norm of typical bodily forms.
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Similarly, regularization based on a function approximating the L0.5 norm was introduced in order to promote a more sparse solution for the displacement fields.
From now on, we apply the proposed methods for approximating the minimum-norm solution of convex function and to split feasibility problems.
Several concrete examples for approximating the ℓ 0-norm are provided at the end of this section.
Our approach is to obtain a sequence of optimization problems by successively approximating the ℓ 0-norm and to solve resulting problems by exploiting the proximity operator.
Our approach for dealing with our proposed model is to obtain a sequence of optimization problems by successively approximating the ℓ 0-norm and to solve resulting problems by exploiting the proximity operator [11].
We also note that the method of proof of Theorem 3.1 provides the following theorem for approximating the common minimum-norm point of the solution set of a variational inequality problem for monotone mapping and fixed point set of a continuous pseudocontractive mapping.
where F is some continuous function that approximates the ℓ0 norm.
This equation was found by approximating (vec {g}) as having no divergence-free part, and approximating the L ∞ part of the ∗-norm in Eq. 2 with the square of the L 2-norm of the same function.
Approximating the color is fine.
The authors incorporated into the classical super-resolution formulation a feature-sensitive prior that approximates the L 1 norm near edges, and this helps to efficiently highlight these critical features.
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