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The sparsity of the representatives is controlled by a regularization parameter based on both spatial and temporal dissimilarities.
The phase field model replaces the sharp discontinuities with a scalar damage field representing the diffuse crack topology through controlling the amount of diffusion by a regularization parameter.
We used the maximum entropy principle calculation of the program to find this estimated distribution; thus, the result was the closest to a uniform distribution with a mean that was closest to the observed mean value from known occurrences, achieved by a regularization parameter.
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In general, regularization techniques involve an addition of a second term that can be adjusted to minimize image artifacts from experimental noise by controlling a regularization parameter at the cost of reducing image spatial resolution.
Equivalently the estimator is the solution of the following minimization problem: (3) where λ≥0 is a regularization parameter specified by user that controls the size of the estimated neighborhood, and hence the sparsity of the network.
The marker effects are obtained by solving the optimization problem, where is a regularization parameter.
λ is a regularization parameter.
where τ is a regularization parameter.
where ?LP?>?0 is a regularization parameter.
(4.1) where (alpha>0) is a regularization parameter.
where s is a regularization parameter.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com