During
the last decade, artificial neural networks have gained an increasing popularity
in several fields of chemistry [46]-[49], whereby the variety of applications
in chemistry is best illustrated in a book written by Zupan and Gasteiger [50].
In the field of multivariate calibration, the class of the multilayer feedforward
backpropagation networks is most popular as they allow calibrating relationships,
which are linear and nonlinear, and as no assumption of a specific type of model
is needed [51]-[55].
In this section, the basics of the multilayer feedforward backpropagation neural
networks are briefly explained and then the issues, which are of interest for
this study, are introduced. A very detailed discussion of neural networks in
multivariate calibration can be found in an excellent tutorial by Despagne and
Massart [8]. More information about the mathematical background
and about other neural network topologies can be found in textbooks [56]-[58].