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Present indirect approaches for solving such interval optimization models by converting them into deterministic ones will result in the loss of uncertainty information and deviate from the original intention of realistically modeling engineering optimization problems.
The ideas are to properly formulate discrete-time MIMO signal models by converting real multirate users into single-rate virtual users, followed by the use of FKMA for extraction of virtual users' data sequences associated with the desired user, and recovery of the data sequence of the desired user from estimated virtual users' data sequences.
The unit was subsequently allocated Mk.21 trainers; GAF built seven of these dual-control models by converting five early Mk.20s and two British-built B.2 bombers.
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The third step was to translate the structural model to an electromagnetic analysis model by converting the tetrahedral body elements of the structural model into triangular surface elements, which were necessary for the electromagnetic analysis.
The tool uses the SAL language to create an intermediate model, by converting the Simulink model into a formal model of finite states, translating the specifications and the high level testing requirements into formal properties by the use of linear temporal logic (LTL).
Here we generalize this model by converting differential equations into integral equations with adjustable kernel functions.
In this paper we generalize the additive regulation model by converting differential equations into integral equations with adjustable kernel functions.
Each thresholded HR-pQCT whole bone image and trabecular bone compartment image of the distal radius and tibia was converted to a µFE model by converting each voxel to an eight-node brick element.
We transform this generative multivariate normal distribution into a discriminative model by converting the probability to log space and using a generalized linear model y | d | = ω 0 | d | + ω 1 | d | l o g (p (r.
If the sample has a dynamic aberration, this effect becomes more severe, which can be modeled by converting s f to s f (t n ) in the Eq. (A1), although s f (t n ) is not predictable.
The task of detecting trigger words can be performed with a CRF model by converting the task to a sequence prediction problem, in which the trigger sequences are represented with the 'IOB2' representation (Sang and Veenstra, 1999).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com