zscore

 ZSCORE removes the mean and normalizes the data 
 to a variance of 1. Can be used for Pre-Whitening of the data, too. 

 [z,r,m] = zscore(x,DIM)
   z   z-score of x along dimension DIM
   r   is the inverse of the standard deviation
   m   is the mean of x

 The data x can be reconstrated with 
     x = z*diag(1./r) + repmat(m,size(z)./size(m))  
     z = x*diag(r) - repmat(m.*v,size(z)./size(m))  

 DIM    dimension
    1: STATS of columns
    2: STATS of rows
    default or []: first DIMENSION, with more than 1 element

 see also: SUMSKIPNAN, MEAN, STD, DETREND

 REFERENCE(S):
 [1] http://mathworld.wolfram.com/z-Score.html