Journal
NEURON
Volume 102, Issue 2, Pages 280-293Publisher
CELL PRESS
DOI: 10.1016/j.neuron.2019.02.039
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Funding
- EU H2020-ICT grant [644732]
- Israel Science Foundation (ISF) [390/12]
- ERC [GA-340063]
- [ANR-10-LABX-0087 IEC]
- [ANR-10-IDEX-0001-02 PSL*]
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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.
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