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The first part of this tutorial describes the deterministic modeling and model reduction techniques, as applied to the class of biochemical reactions specific to molecular cell biology.
Different model reduction techniques are available for descriptor systems.
Model reduction techniques are widely used in controller design.
Hence, these methods are often termed as model reduction techniques.
Model reduction techniques can be extremely useful to keep model dimensions to a minimum.
Generally, model reduction techniques approximate the higher order systems for whole frequency range.
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In this section, we outline a model reduction technique widely used in physiological models that are modelled as slow-fast systems, and find conditions under which the use of this technique is justified.
Using a model reduction technique, the EOTF is further approximated to the reduced-order form.
This unconfined model reduction technique is based on Galerkin projection and the Newton formulation of MODFLOW.
Two numerical examples are included to illustrate the effectiveness of the new model reduction technique.
In this article, we show when such a physiological model reduction technique in a slow-fast system is mathematically justified.
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model adaptation techniques
model selection techniques
model reduction methods
model calibration techniques
model inversion techniques
model comparison techniques
model transformation techniques
model alignment techniques
model evaluation techniques
model regression techniques
model approximation techniques
model compensation techniques
model registration techniques
model reduction algorithms
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