Yes, the rmoutliers function will do the trick. After removing the top and bottom 5% of the values, the vectors below are reduced from 100 elements each to 90 elements each.
% test data
x = rand(1,100);
y = rand(1,100);
z = rand(1,100);
D = rand(1,100);
[D, TF] = rmoutliers(D, 'percentiles', [5 95]);
x(TF) = [];
y(TF) = [];
z(TF) = [];
whos