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This weight factor is utilized for avoiding the oversmooth due to the regularization term.
This is attributed to the regularization strategy of the SVM classifier with Kalman post-processing.
The obtained dislocation fields are non-singular due to the regularization of the classical singular fields.
This range also indicates the sensitivity degree of the damage identification problem to the regularization parameter.
Two different approaches to the regularization are discussed and compared on test problems.
Therefore, to employ computational methods which are designed for strongly monotone variational inequalities, we resort to the regularization.
Similar(29)
This allows us to optimize the regularization to compromise between the minimization of these two quantities.
Later, several authors suggested to use prior knowledge to define Tt to allow the regularization of all variables in one biological group together rather then individual regularization for each variable [ 30, 31].
We used a search procedure to modify the regularization parameter to obtain inferences for all sparsity levels.
Here, note that both of these two approaches provide advantages such as increased resolution, reduced sidelobes, and reduced speckle in the imaging side thanks to the regularization-based image formation, which can alleviate challenges caused by incomplete data or sparse apertures [15] as well.
Then, to estimate the explicit learning rate, one needs to estimate the regularization errors (see, e.g., [4, 7, 9, 14]).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com