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Additionally, a mathematical method is suggested for model identification that solves a priori flux identifiability problems regarding C labeling experiments in terms of model linearization.
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Partially automated regularisation procedure is suggested for the model parameters identification.
SVC is suggested for subspace identification methods.
Preliminary results yield promising average correlation levels between predicted and real movement, suggesting that CLINATEC® model identification methods are relevant for hand movement decoding from MEG signals in human subjects.
Indirect recursive identification algorithms have been suggested for robust control design in the literature.
A suggested strategy for identification is a routine postoperative esophageal transit study.
Processes suggested in this model include identification, live collection and analysis, and static collection and analysis [47].
The model identification (e.g. System identification-theory for the user.
This includes methods for model quality control, data and model integration, model comparison and model identification.
A new look at the statistical model identification.
Model identification and model selection.
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