Classical Learning Systems

For the implementation of information processes, some kind of fundamental physical systems which transform signals and patterns are needed. In the simplest cases the relationship between representations of information at input and output, respectively, can be described in terms of a transformation function. Such systems are often named filters. The classical learning networks are signal-transforming systems the parameters of which are slowly changed by the effect of signal energy. Such systems are also named adaptive,and they may automatically adjust themselves to become optimally selective with respect to certain signal or pattern statistics.