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The problem of the extraction of the useful signal from a noisy background is one of
the most important areas of signal processing. Order Statistic (OS) smoothers, based on
amplitude ordering of signal samples, have been shown to offer an effective alternative
to linear smoothers. It is the case particularly when there is uncertainty concerning
noise statistics, or when the useful signal possesses local features such as sharp edges.
In this paper we consider some linear and nonlinear (OS) smoothers, and propose a new
smoothing algorithm. Simulation results are presented to illustrate the performance of
the proposed smoother
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