2016
DOI: 10.1186/s13634-016-0383-6
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Generalized Hampel Filters

Abstract: The standard median filter based on a symmetric moving window has only one tuning parameter: the window width. Despite this limitation, this filter has proven extremely useful and has motivated a number of extensions: weighted median filters, recursive median filters, and various cascade structures. The Hampel filter is a member of the class of decsion filters that replaces the central value in the data window with the median if it lies far enough from the median to be deemed an outlier. This filter depends on… Show more

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Cited by 174 publications
(91 citation statements)
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“…We took a minimalist approach to cleaning the pupil data. Data that the Gazepoint GP3 system identified as poor were replaced using linear interpolation, and within‐subject outliers were corrected using a Hampel filter (see Pearson, Neubo, Astola, & Gabbouj, ). Linear interpolation was done using the zoo package (Zeileis, Grothendieck, Ryan, & Andrews, ) in R (R Development Core Team, ).…”
Section: Methodsmentioning
confidence: 99%
“…We took a minimalist approach to cleaning the pupil data. Data that the Gazepoint GP3 system identified as poor were replaced using linear interpolation, and within‐subject outliers were corrected using a Hampel filter (see Pearson, Neubo, Astola, & Gabbouj, ). Linear interpolation was done using the zoo package (Zeileis, Grothendieck, Ryan, & Andrews, ) in R (R Development Core Team, ).…”
Section: Methodsmentioning
confidence: 99%
“…Since we employ a low-pass filter to remove the part of the spectrum where the signal is dominated by the noise, this feature does not impact the present study. Implementation of a spectral Hampel filter and time series reconstruction: To eliminate these spikes, we adapt a decision-based filter known as Hampel filter, a well-known technique in the signal-processing community for removing outliers from a signal (Davies & Gather 1993;Liu et al 2004;Pearson et al 2016). We apply the filter in frequency spectra domain to remove the spikes, while maintaining the original phase information.…”
Section: Fpi Moments In the Solar Windmentioning
confidence: 99%
“…We established experimentally that resampling the data to the minute barely loses any information from the signal, while still substantially reducing the size of the dataset. Third, to avoid the amplification of clear outliers, they are removed with a Hampel filter [14]. Fourth, we focus on the 'exponential deterioration stage' of the filter's life cycle [5], because-according to the company-the start of that stage is early enough to be able to act on time, and because it provides us with a dataset that is suitable for similarity-based RUL prediction techniques.…”
Section: Case Studymentioning
confidence: 99%