Naslov
Denoising Accuracy of Adaptive ICI-Based Estimators With Regards to Sampling Rate

Autori
Lerga Jonatan ; Saulig, Nicoletta ; Žuškin, Martina ; Panjkota, Ante

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
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, 2019, 1-6

ISBN
978-953-290-091-0

Skup
4th International Conference on Smart and Sustainable Technologies (SpliTech 2019)

Mjesto i datum
Split, Hrvatska, 18.06.2019. - 21.06.2019

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Intersection of confidence intervals (ICI) rule ; relative intersection of confidence intervals (ICI) rule ; signal denoising ; sampling rate

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Matematika, Računarstvo

POVEZANOST RADA