Lernmatrix
Lernmatrix is a special type of artificial neural network architecture, similar to associative memory, invented around 1960 by Karl Steinbuch, a pioneer in computer science and ANNs.
This model for learning systems could establish complex associations between certain sets of characteristics and their meanings.
Function
The Lernmatrix generally consists of n "characteristic lines" and m "meaning lines," where each characteristic line is connected to each meaning line, similar to how neurons in the brain are connected by synapses..To train a Lernmatrix, values are specified on the corresponding characteristic and meaning lines ; then the connections between all pairs of characteristic and meaning lines are strengthened by the Hebb rule. A trained Lernmatrix, when given a specific input on the characteristic lines, activates the corresponding meaning lines. In modern language, it is a linear projection module.
By appropriately interconnecting several Lernmatrices, a switching system can be built that, after completing certain training phases, is ultimately able to automatically determine the most probable associated meaning for an input sequence of features.