In signal processing, Lulu smoothing is a nonlinear mathematical technique for removing impulsive noise from a data sequence such as a time series. It is a nonlinear equivalent to taking a moving average (or other smoothing technique) of a time series, and is similar to other nonlinear smoothing techniques, such as Tukey or median smoothing.[1]
LULU smoothers are compared in detail to median smoothers by Jankowitz and found to be superior in some aspects, particularly in mathematical properties like idempotence.[2]