Computationally effective algorithm for robust weighted averaging

IEEE Transactions on Bio-medical Engineering
Jacek M Leski, Adam Gacek

Abstract

One of the greatest disadvantages of the weighted signal averaging method is its sensitivity to the presence of noise and outliers in data and the need to estimate the noise variance in all signal cycles. The robust weighted averaging method based on the epsilon-insensitive loss function is free of these disadvantages, but has a very high computational burden and requires a choice of the insensitivity parameter epsilon. In this study, a new computationally effective algorithm for robust weighted averaging with automatic adjustment of the insensitivity parameter is introduced.

References

Apr 1, 1992·IEEE Transactions on Bio-medical Engineering·C E Davila, M S Mobin
May 1, 1986·IEEE Transactions on Bio-medical Engineering·P BergveldJ H Peuscher
Aug 1, 2002·IEEE Transactions on Bio-medical Engineering·Jacek M Leski
Mar 6, 2003·IEEE Transactions on Bio-medical Engineering·Paulo Roberto B BarbosaJurandir Nadal
Feb 6, 2008·IEEE Transactions on Neural Networks·A Navia-VázquezA R Figueiras-Vidal

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Citations

Oct 12, 2007·IEEE Transactions on Bio-medical Engineering·Stephan WaldertHubert Preissl
May 13, 2015·Journal of Electromyography and Kinesiology : Official Journal of the International Society of Electrophysiological Kinesiology·Armando MalandaLuis Gila
Dec 14, 2018·Physiological Measurement·Fahimeh Jamshidian-Tehrani, Reza Sameni
Nov 5, 2016·Physiological Measurement·Hadis Biglari, Reza Sameni

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