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For the AR estimator, the estimated model order M for the minimum error is presented.
By updating the parameters of the estimated model based on prediction error, the estimated model approaches the real plant gradually in real-time.
Left: power spectrum of the 'true' model (black), the estimated model without polar gap treatment (red), and the estimated model with the polar gap processing (blue).
The LMR-LRT compares the estimated model with a model with one class less than the estimated model.
are found to be statistically significant in the estimated model.
Then, the estimated model could have better predictive ability.
The estimated model parameters were checked for logical validity.
The estimated model parameters are presented in Table 4.
The estimated model parameters described the experimental data accurately.
The estimated model parameters were then validated against other data from a similar region and roadway.
Also, the proposed algorithm overcomes the problem of loss of controllability of the estimated model.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com