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.
Paper of the month
Nelken's Lab: Filters: When, Why, and How (Not) to Use Them
Neuron, Volume 102, Issue 2, 2019, Pages 280-293, ISSN 0896-6273, (2019)