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Filters: When, Why, and How (Not) to Use Them

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, explains what is a filter, what problems are to be expected when using them, how to choose the right filter, or 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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Submitted on : Monday, January 4, 2021 - 1:41:58 PM
Last modification on : Friday, October 15, 2021 - 1:40:46 PM
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Alain de Cheveigné, Israel Nelken. Filters: When, Why, and How (Not) to Use Them. Neuron, Elsevier, 2019, 102 (2), pp.280-293. ⟨10.1016/j.neuron.2019.02.039⟩. ⟨hal-02399697⟩



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