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function Y=stdmean(X,A) 
%STDMEAN Weighted average based on error from the mean 
%	stdmean(X,A) 
%	This calculates a weighted mean based on how clusted the 
%	data is. Each value is weighted inversely by the number 
%	of standard deviations it is to the mean (Z). 
%	A is the power to weight the Z by, for example: 
%	if A = -1, then the values are weighted by Z^-1. 
%	if A = -2, then the values are weighted by Z^-2. 
%	A can be a fractional number. 
%	Note : A is an optional parameter with default of -2 
% 
%	For vectors, STDMEAN(X)  is the mean value of the elements in X. 
% 	For matrices, STDMEAN(X) is a row vector containing the mean value 
% 	of each column. 
% 
%	Early tested have shown that using the stdmean does not 
%	improve the performance, or reduce phase error . 
if nargin < 2, 
	A = -2; 
end 
if size(X,1) == 1, 
	Z = (X - mean(X))./std(X);	%Find number of std each point 
					%is away from mean. 
	W = abs((Z+0.01).^(A));		%Calc the weighting factor of each point 
	Y = sum(X.*W)./sum(W); 
else 
	for k = 1:size(X,2), 
		Z(:,k) = (X(:,k) - mean(X(:,k)))./std(X(:,k)); 
					%Find number of std each point 
					%is away from mean. 
		W(:,k) = abs((Z(:,k)+0.01).^(A)); 
					%Calc the weighting factor of each point 
		Y(:,k) = sum((X(:,k).*W(:,k)))./sum(W(:,k)); 
	end 
end