De Cheveigne, A;
Nelken, I;
(2019)
Filters: why, when and how (not) to use them.
Neuron
, 102
(2)
pp. 280-293.
10.1016/j.neuron.2019.02.039.
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Abstract
Filters are commonly used to reduce noise and improve data quality. Filter theory is part of a scientist’s training, yet the impact of filters on interpreting data is not always fully appreciated. This paper reviews the issue and explains what a filter is, what problems are to be expected when using them, how to choose the right filter, and how to avoid filtering by using alternative tools. Time-frequency analysis shares some of the same problems that filters have, particularly in the case of wavelet transforms. We recommend reporting filter characteristics with sufficient details, including a plot of the impulse or step response as an inset.
| Type: | Article |
|---|---|
| Title: | Filters: why, when and how (not) to use them |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.neuron.2019.02.039 |
| Publisher version: | https://doi.org/10.1016/j.neuron.2019.02.039 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | filter,distortions, Fourier analysis, time-frequency representation, ringing, causality impulse, response, oscillations |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > The Ear Institute |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10067236 |
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