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

Alain de Cheveigné (1, 2) , Israel Nelken

1 DEC - Département d'Etudes Cognitives - ENS Paris
2 LSP - Laboratoire des systèmes perceptifs

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.

Mots clés: filter; artifact; Fourier analysis; time-frequency representation; ringing; causality; impulse response; oscillations

Domaines: Neurosciences

Alain de Cheveigné, Israel Nelken. Filters: When, Why, and How (Not) to Use Them. Neuron, 2019, 102 (2), pp.280-293. ⟨10.1016/j.neuron.2019.02.039⟩. ⟨hal-02399697⟩