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Since the Taylor-series expansion is used in estimating position errors, Step 3 should be applied repeatedly in order to obtain higher estimation accuracy with x mo compensated by Δx m (which is estimated in the former iteration) in each iteration.
This strategy has the benefit of attaining higher estimation accuracy only when necessary without causing excessive computation load.
Simulation results show that the proposed algorithm has higher estimation accuracy when the signal to noise ratio (SNR) is above 3 dB.
The results also illustrate that the CCANN models are superior to the BPANN and GRNN models and lead to higher estimation accuracy.
However, since Taylor-series expansion causes approximation errors, position error estimation should be iterated in order to obtain higher estimation accuracy.
According to the simulation results in Section 4.3, in both low SNR and high SNR, the proposed algorithm still has higher estimation accuracy than CED algorithm.
Similar(45)
In the first method, the lower lags of the auto-covariance function are used to estimate the observed noise variance with high estimation accuracy, but it is valid only when the AR order is greater than the MA order.
The results show high estimation accuracy.
Thus, We can expect a high estimation accuracy in a high-SNR case.
The methods imply high estimation accuracy for selecting candidate siRNA sequences.
The experimental results indicate that the presented model achieves high estimation accuracy and leads to effective prediction.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com