Denoising Accuracy of Adaptive ICI-Based Estimators With Regards to Sampling Rate (CROSBI ID 678026)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Lerga Jonatan ; Saulig, Nicoletta ; Žuškin, Martina ; Panjkota, Ante
engleski
Denoising Accuracy of Adaptive ICI-Based Estimators With Regards to Sampling Rate
This paper presents study on denoising accuracy of adaptive temporal filtering methods based on the intersection of confidence intervals (ICI) rule and relative intersection of confidence intervals (RICI) rule with regards to signal sampling rate. The original ICI-based and the improved RICI-based method were tested on four signal classes for a range of signal to noise ratios (SNRs). Denoising accuracy, with respect to signal sampling rate, was measured in terms of the reductions in root mean squared error (RMSE) and mean absolute error (MAE). Extensive simulations showed that the data- driven RICI method outperformed the original ICI method reducing the RSME by up 79.6% and the MAE by up to 86.1%. It is important to note that both methods, especially the RICI method, exhibit significant estimation accuracy improvement in case of signals with higher sampling rates.
Intersection of confidence intervals (ICI) rule ; relative intersection of confidence intervals (ICI) rule ; signal denoising ; sampling rate
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Podaci o prilogu
1-6.
2019.
objavljeno
10.23919/SpliTech.2019.8783082
Podaci o matičnoj publikaciji
4th International Conference on Smart and Sustainable Technologies (SpliTech)
Perković, Toni ; Vukojević, Katarina ; Rodrigues, Joel J. P. C. ; Nižetić, Sandro ; Patrono, Luigi ; Šolić, Petar
Split: Fakultet elektrotehnike, strojarstva i brodogradnje Sveučilišta u Splitu
978-953-290-091-0
Podaci o skupu
4th International Conference on Smart and Sustainable Technologies - SpliTech2019
predavanje
18.06.2019-21.06.2019
Split, Hrvatska; Bol, Hrvatska
Povezanost rada
Matematika, Računarstvo