Trimmed estimators for robust averaging of event-related potentialsстатья
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Дата последнего поиска статьи во внешних источниках: 5 июня 2019 г.
Авторы:
Leonowicz Z. ,
Karvanen J. ,
Shishkin S.L.
Журнал:
Journal of Neuroscience Methods
Том:
142
Номер:
1
Год издания:
2005
Издательство:
Elsevier BV
Местоположение издательства:
Netherlands
Первая страница:
17
Последняя страница:
26
DOI:
10.1016/j.jneumeth.2004.07.008
Аннотация:
Averaging (in statistical terms, estimation of the location of data) is one of the most commonly used procedures in neuroscience and the basic procedure for obtaining event-related potentials (ERP). Only the arithmetic mean is routinely used in the current practice of ERP research, though its sensitivity to outliers is well-known. Weighted averaging is sometimes used as a more robust procedure, however, it can be not sufficiently appropriate when the signal is nonstationary within a trial. Trimmed estimators provide an alternative way to average data. In this paper, a number of such location estimators (trimmed mean, Winsorized mean and recently introduced trimmed L-mean) are reviewed, as well as arithmetic mean and median. A new robust location estimator tanh, which allows the data-dependent optimization, is proposed for averaging of small number of trials. The possibilities to improve signal-to-noise ratio (SNR) of averaged waveforms using trimmed location estimators are demonstrated for epochs randomly drawn from a set of real auditory evoked potential data. © 2004 Elsevier B.V. All rights reserved.
Добавил в систему:
Шишкин Сергей Львович