A new phenomenological approach to the analysis of complex membrane structu
res and surfaces and the processing of corresponding experimental data obta
ined, for example, from the roughness study is presented. The methodology i
s based on a postulate about the crucial information contained in non-regul
arities of measured spatial dynamic variables, as well as on the acceptance
of a new scaling equation. Accordingly, power spectra and structural funct
ions of different orders are determined by non-regularities of different ty
pes resulting from dynamical spikes and jumps of the measured variables. It
is also shown that equations for power spectra as well as for structural f
unctions are the same at every spatial-temporal level of the system under c
onsideration. It is demonstrated that multi-parametric invariant relationsh
ips characterize a new kind of self-similarity. Appropriate phenomenologica
l parameters are introduced. It is shown that these parameters characterize
self-similarity in the rate of loss of correlation links between non-regul
arities of one type as well as self-similarity in the dynamics of memory lo
ss in the dynamic variable, as the spatial distance from any fixed point in
creases, for non-regularities of a second type. An algorithm is developed w
hich makes it possible to obtain as many parameters as it is necessary for
the characterization of the dynamic state of a system and changes of its st
ate during evolution. Application of this approach to the analysis of surfa
ce roughness of a perfluorinated cation-exchange membrane coated with plati
num layer is demonstrated. (C) 2000 Elsevier Science B.V. All rights reserv
ed.