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Minimum feature dimensions of 500 nm in polysilicon and 200 nm in LS-SiN is presented.
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The common subspace dimension is bounded by the minimum feature dimension whether it from the source or target feature space as to prevent overfitting.
Because of being compatible with conventional microelectronics and minimum feature size approaching to atomistic dimensions, silicon-based molecular electronics has emerged as a viable option [4, 5].
3 feature dimensions in T test and 5 feature dimensions in Kolmogorov Smirnov test are thought as different-distribution feature.
The first assumption is about the dependency of certain feature dimension to the other feature dimensions, and the second is about the RTF of feature dimension.
They claimed a comparable performance with much reduced feature dimensions.
There are 25 feature dimensions in total, as follows: 1.
Semantic roles/relations may categorize into different feature dimensions.
Some indiscriminative feature dimensions may be mistakenly selected.
Commonly, activity landscapes depict activity values in 2 feature dimensions.
› The discriminativity of the unselected feature dimensions - the noisier such feature dimensions are, the higher the improvement would be.
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