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However, in order to further study and apply model (1), further rigorous work is needed to investigate the mathematical properties of the model.
Another approach is to apply model reduction to obtain a smaller MDP and then solve it using an off-the-shelf MDP solver [6].
The goal is to use the Simulink model, high-level requirements and test specifications to apply model checking techniques for the generation of test data.
It became very popular to apply model predictive controllers (MPCs) to reduce the quantity of off-specification products, however most of them use linear models for prediction.
In this paper, we apply model compression techniques to the problem of semantic segmentation, which is one of the most challenging problems in computer vision.
While many languages for model manipulation exist (e.g., for model transformation or code generation), there is a lack of frameworks to define and apply model mutations.
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Traditional methods apply model-based nonlinear feedforward to compensate the friction, thus requiring closed loop stability and safety constraint considerations.
This work is related to a large corpus of researches that apply model-driven development (MDD) to specify the user interaction for multi-device UI modeling.
In particular, we apply model-checking, an automated and exhaustive algorithmic technique, to check whether temporal properties are satisfied on all the possible behaviours of the system.
Another important approach to further speed-up the simulation is to apply model-order reduction to the circuit used as input for the simulator such that accuracy is not compromised and simulation time is drastically reduced [10, 18, 19].
Methods that approximately analyze the design and try to detect as many design bugs as possible are needed in cases where it is impossible to apply model-checking-type state-based analysis methods to such design descriptions.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com