In this paper we introduce a new design strategy for SFWO (sampled function weighted order) filters based on approximation theory. It is shown that with a good choice of noise tail-length estimator and a good approximation of the relation between this estimate and filter parameters, the adaptive SFWO filter gives very promising results when the noise type is unknown or varies with time. For this use, we also introduced a new tail-length estimator based on robust statistics.
['R. Oten', 'R.J.P. de Figueiredo']
Adaptive SFWO filter design