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To obtain an implementation friendly architecture, we propose approximations for the mean and variance estimation functions within the algorithm.
Exploit the strategy described in Section 3.1 (see Fig. 3) to obtain an implementation of the pth-order kernel of interest in the form of a parallel structure composed of second-order kernels.
In Section 5.4, we proposed a relaxation of the prior distribution (Gaussian instead of Laplace) in order to obtain an implementation of Algorithm 1 that features a lower computational complexity and better numerical stability.
In this context, the proposed approach can be summarized as follows: i) Exploit the strategy described in Section 3.1 (see Fig. 3) to obtain an implementation of the pth-order kernel of interest in the form of a parallel structure composed of second-order kernels.
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These toolboxes allow obtaining an implementation of the controllers over several Operating Systems.
To obtain an efficient implementation, a hierarchical tensor product basis in space and time is proposed.
As a result, we obtain an improved implementation of DTFC, which significantly reduces the levels of steady-state ripple with respect to those typically obtained with conventional implementations of DTFC.
It is noteworthy that despite our best effort, we were unable to obtain an OMNeT++ implementation of an existing QoS routing protocol which performs the admission control process through the opportunistic routing paradigm or even through unipath-based routing.
Rethinking the implementation to obtain a parallel implementation, the instance of Algorithm 1 with block partitioning leads to the Algorithm 5. 1: Robot pose initialization.
To obtain a fast implementation, the process units (reaction tanks and secondary settler) have been implemented as DLLs linked to the Simulink blocks, whereas the model parameters and stoichiometric matrix remain accessible to the user.
In order to use an errors-in-variables noise model, a linear approximation is necessary in order to obtain a fast implementation of the GTLS algorithm.
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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