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Results show that for experimental data, the root mean square estimation error of the estimates of the first two modes was within 6% of the desired values and for the next two modes was within 20% of the desired values.
Figure 6 Root mean square estimation error versus SNR with.
Figure 7 Root mean square estimation error versus tracking frequency with initial.
The evaluation criterion is the root mean square estimation error (RMSE).
(A) Root mean square estimation error and reduction ratio as functions of the uncertainty threshold (20 repetitions are considered).
In particular, in Figure 5(a), the estimation error of the ML-based method is lower than the CRLB because the data length exceeds that,, used in the CRLB. Figure 5 Root mean square estimation error versus SNR with K = 120.
Similar(52)
An inspection of (16) will immediately show that if the convergence does occur, the root mean-squared estimation error at time is such that (18).
Root mean square approximation.
The cross-validation statistics investigated include mean squared estimation error (MSE), root mean squared estimation error (RMSE), mean absolute estimation error (MAE), mean of the root variance of the posterior PDFs (MR), the square of Pearson's correlation coefficient, and the square of Spearman's correlation coefficient.
The performance is measured using the root mean squared estimation error (RMSE) as defined in [28, 32, 26, 27].
Simulation results also demonstrated that the root mean squared estimation errors (RMSEEs) can be reduced by enlarging the bandwidth of a low-pass-filter (LPF) applied in the SC.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com