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Finally, a numerical study of a simplified car dynamics is conducted to demonstrate the capability and effectiveness of the BRB identification models for the modelling and identification of uncertain nonlinear systems.
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For the numerical analysis and identification of the resulting models the simulation environment DIVA is described.
The processed input and output signals are used for the model identification of (1) and (4).
This condition is necessary for the model identification and for a proper reconstruction of the output signal.
The design of the model required the identification of all the OSH factors relevant for SMEs.
For the identification of factors that contribute to the outcomes studied, generalized linear mixed models with patient identification and identification of each individual swab as random effects were used.
Optimal conditions were predicted with the model and tested for the identification of single nucleotide polymorphisms.
This illustrates the potentiality of the parameterized transient model for the identification of multiple leaks.
We created a threshold interval model for the temporal identification of changes in the backscattered intensity.
The initial step for the model development is the identification of a structural homology.
Experimental data from cultivations of Ustilago maydis are used for the model-based parameter identification.
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