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We note that the way in which these model dynamics vary in relation to coupling strength is very similar to the full neural mass model (see [13]).
In the developed model, the constraints on different parameters that enforce appropriate model dynamics vary widely from some very tightly controlled parameters to others that are almost arbitrary.
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In this paper, a generalized Hammerstein model consisting of a static polynomial function in series with time-varying linear model is proposed in order to model the Hammerstein-like multivariable processes whose linear dynamics vary over the operating space.
Again, the predictions about the long-term dynamics vary, not only between models, but between different parameter combinations of the same model.
For nonlinear thermal power plants whose dynamics vary with load demand, a load-dependent exponential ARX (Exp-ARX) model, which can effectively describe the nonlinear properties of the plants, is presented.
For nonlinear thermal power plants whose dynamics vary with load demand, a load-dependent exponential ARX (Exp-ARX) model which can exactly describes the nonlinear properties of the plants is presented.
Growth dynamics vary for different end-markets.
Data traffic dynamics vary significantly in different WSN scenarios.
Pharmaceutical market dynamics vary across Europe due to different regulatory frameworks.
Column dynamics vary with column dimensions and flow rate.
From the fifth generation on, the population dynamics vary between apples.
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