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The Historical and Sampling methods can further reduce the energy emission compared to Default start.
Note that the transform methods can further be split into linear transform methods, like principal component analysis (PCA), independent component analysis (ICA), Gabor transform, and nonlinear transform methods like Kernel PCA (KPCA), local linear embedding (LLE) etc.
Because both smooth and sparse regularization frameworks have been shown to improve the prediction power of unregularized models [1], [3], [8], it is likely that combining features of both methods can further improve the quality of the estimates.
However, both isolation methods can further be improved.
In addition, we found that combining the results of two methods can further improve the performance.
These isolation methods can further complicate GMP-compliant protocols, particularly when performing large-scale expansions.
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In addition, the multiscale method can further improve the results.
Compared with the ERVU method, the PDMSE method can further improve speech quality without decreasing intelligibility.
The weights obtained from the proposed method can further be used for evaluation based on words.
In addition, our hybrid method can further provide accurate detection performance for a variety of manipulations.
The proposed method can further be investigated for various types of medical images and also validated for a multiclass problem.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com