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For model identification, the parameters (and/or constants) for one class are required to be set to zero, such that all the remaining parameters are interpreted as being relative to this class.
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The identification of the parameters εd0, A, B and εdc0 are good.
The introduction of a damping parameter permits the definition of a procedure for the precise identification of the parameters.
This paper describes a method for the identification of the parameters entering into the equations of motion of distributed systems.
A modified form of Littlewood Paley (L P) basis function is used for the identification of the parameters.
Identification of the parameters w i is performed such that the predistorter function approximates the channel post-inverse.
Each of the series is modeled as an ARIMA p, 1, q) process, using the Box and Jenkins (1976) method for the identification of the parameters.
Another issue that makes the identification of the parameters of these models difficult is the fact that the log-likelihoods are generally multimodal.
In this context, the identification of the parameters influencing model dynamics can be advantageous to increase model accuracy and to provide hints in designing wet experiments.
For these types of problems, where different parameter values can result in similar activity, identification of the parameters through the data can be ambiguous.
The work cycle consists of one working configuration (boldsymbol {q}^{mathrm{work}} in mathbb{R}^{6}) after which the re-identification of the parameters is performed with 60 measurement configurations.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com