📄 selectivemedian.m
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function [y] = SelectiveMedian(x, wla, pfa)%SelectiveMedian: Selective Median Filter %% [y] = SelectiveMedian(x,wl,pf)%% x Input signal% wl Width of the sliding window in samples (odd integer).% Default=11.% pf Plot format: 0=none (default), 1=screen.%% y Filtered signal%% Filters the signal using a Selective Median Filter. A window% of width wl is placed at the beginning of the input vector. The% input values within the window are divided into three groups:% the central value, the values before the central value (lower % values), and the values after the central value (upper values). % The median of the lower values and the median of the upper values % are then computed and compared to the central value. The one whose% value is closest to the central value is stored in the output % vector y. If both of them are at the same distance from the central % value, the median of the whole window is stored in the output vector% y. The same procedure is repeated as the window slides through the% data, advancing one sample at a time.%% Example: Filter the nonlinear filters test signal using a Selective % Median Filter with wl = 31, and plot the results.%% load NFSignal.mat;% [y] = SelectiveMedian(x, 31, 1);%% Astola, J. and Kuosmanen, P., "Fundamentals of Nonlinear Digital % Filtering," CRC Press, pp.108-109, 1997.%% Version 1.02 CC%% See also SelectiveAverage and ComparisonSelection.
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