The present work discusses the many attributes - classified as observa
ble, intrinsic or hidden - which can be conceived for any complex mult
icomponent chromatogram. Discussion ensues on how to decode such chrom
atograms, i.e. determining the intrinsic and/or hidden attributes from
those which can be observed. There are two main steps. The first is b
ased on Fourier Analysis (FA) and determines the intrinsic attributes:
i.e., the number of single components which can be detected; their di
stribution over the available chromatographic space and peak capacity.
The second evaluates the hid den attributes: i.e., the effects of inc
omplete separation, the number of peaks created by one or more single
components as well as their degree of purity. The hidden attributes ca
n be obtained by applying the theory of Statistical Degree of peak Ove
rlapping (SDO) and the paper goes into the extent to which the SDO ste
p depends on the FA results. In addition, the role Exponential distrib
ution plays as a point of reference for the distribution of both singl
e component peak position interdistances and peak heights is discussed
. Finally, a simplified graphical FA procedure is presented and the ma
in achievements in this field are reviewed.