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This paper describes an interactive tool focused on teaching and learning basic concepts about modelling and identification.
The paper aims at discussing neuro-fuzzy models, modelling and identification issues useful in practical applications in process control, decision making and classification, when modelling system static and dynamic characteristics.
The supported research mainly focused on embedded real-time platforms for robotics and industrial automation; modelling and identification; basic navigation, guidance and control; straight line and generic path following; cooperative mission control and path-following.
Moreover, an experimental modelling and identification of the cantilever parameters are presented.
This paper studies the modelling and identification problems for multi-input single-output (MISO) systems with colored noises.
Mathematical modelling and identification of systems, where the structure of some equations is unknown, is a difficult task.
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Neural network (NN) approaches have been widely applied for modeling and identification of nonlinear multiple-input multiple-output (MIMO) systems.
This paper concerns on the aluminum foam material modeling and identification of constitutive parameters at high strain rates.
IRMA is a synthetic network constructed in yeast and proposed as a benchmark for modeling and identification approaches (Cantone et al., 2009).
Mechanical design, dynamics modeling, and system identification of the surgical robot are conducted.
There are mainly two kinds of CNN models, i.e., verification models and identification models.
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