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This makes the method very flexible, since there is no need to recompute the energy coefficients or have any knowledge of the filter kernel.
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Due to the inherent nature of gradient method, the proposed method is very flexible and it can tackle the designs with composite objectives, which are more challenging and often intractable for the existing methods.
The suggested automation method is very flexible.
This method is very flexible and promising as it is relatively simple, reproducible, and economically feasible.
The method is very flexible as any type of prior distribution can be used.
In turn, the method is very flexible and allows to deal with unstructured meshes.
The CCs method is very flexible in terms of defining the number of cancellation subcarriers and their power levels.
The method is very flexible, not costly in terms of computer time, and can be adapted tovarious situations.
The proposed method is very flexible and is easily extended to complex multilocus-analysis settings involving covariates.
This method is very flexible for rapid prototyping, but is comparatively slow due to the sequential machining.
The proposed method is very flexible in the sense that it can be directly applied with any type of frame-wise quantizer.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com