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In addition, a different regularization scheme is applied to the time changing part of the model.
In addition, a frequency-dependent regularization scheme is adopted in designing the CCS inverse filters.
Their regularization scheme leads to low SH orders having more weights than high SH orders.
To implement the above regularization scheme, we need to specify a neighborhood system.
This important property can be exploited to develop a new regularization scheme.
During the optimization, a mesh regularization scheme is employed to avoid excessive mesh distortion, which comes from significant design changes.
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Corresponding regularization schemes have been proposed to produce stable results.
Proof: Two regularization schemes are equivalent if they have the same filter factors.
Given this setup, we develop a framework for low-rank matrix estimation that allows us to transform noise models into regularization schemes via a simple parametric bootstrap.
The filter factors of the TSVD and the Tikhonov regularization schemes are depicted in Figure 2. Figure 2 Filter factors of the Tikhonov and TSVD regularization methods.
The contextual modeling with latent aspects that we present in this paper can be conveniently integrated with traditional spatial regularization schemes.
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