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An additive model set is used to describe the uncertainty arising from the wide range of the vehicle operating situations.
By model interpolation, we mean that the target synthesis model set is a convex combination of multiple synthesis model sets.
Identification of the optimal model set is a NP-hard problem anc alternative algorithms are investigated, simpler to be computed, at the expense of identification accuracy degradation.
Afterwards, every speaker's utterances are parameterized with the estimated best warp factor and then the HMM model set is re-estimated from this warped feature set.
After analyzing the model fitness, the best model set is determined as ARIMA ( left( {0,1,0} right) times left( {0,1,1} right)^{12} ).
Find the speaker whose neutral model set is closest to ϕ T, l ∗ = arg min l ∈ { 1, …, L } d M ( ϕ T, ϕ l ).
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The model set was tuned to the data of each patient at baseline conditions.
The model set was evaluated in 12 and 5 patients on volume and pressure support respectively.
Let the data required for training an SSS model set be D t, and for adapting a model set be D a, where we often have D a
By applying EC-PLS, a model set was developed, which consists of various models that were equivalent to the optimal model.
Response predictions supported by the subsets of a model set are integrated into a composite prediction using the disjunctive rule of combination.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com