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A novel Bayesian paradigm for the identification of output error models has recently been proposed in which, in place of postulating finite-dimensional models of the system transfer function, the system impulse response is searched for within an infinite-dimensional space.
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We propose to use the proper orthogonal decomposition approach with re-identification of output equations to obtain a reduced-order model of the original system.
This paper considers the robust algorithm for identification of OE (output error) model with constrained output in presence of non-Gaussian noises.
Note again, our identification of input-output equivalence with "behaving identically".
It is hence typical to employ intermediate outputs/services in hospital cost or production analyses (e.g. patient days, number of cases, etc).. Furthermore, delivery of primary health care is diverse and there is little consensus on a common operational definition or on the identification of inputs, outputs and processes [ 34].
Moreover, disturbance rejection and robustness tests admit capability of the method for online dynamic identification in the presence of output and dynamic perturbation.
This paper examines the identification of a single-output two-input system.
Note that the Kalman filter-based approaches have also been generalized for the efficient identification of multiple-input/multiple-output systems [43].
The identification of an input-output model of a patient with Type 1 Diabetes Mellitus (T1DM) in intensive therapy regimen, i.e. continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) is presented.
For large and complex networks, such as the budding yeast cell cycle, the identification of such input-output relationships can be challenging and counterintuitive [ 1].
Under different conditions, the application of identification method output promising results.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com