Lernmatrix (German for "learning matrix") is a special type of artificial neural network (ANN) architecture, similar to associative memory , invented around 1960 by Karl Steinbuch , a pioneer in computer science and ANNs.
2-501: This model for learning systems could establish complex associations between certain sets of characteristics (e.g., letters of an alphabet) and their meanings. 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 . (This can be realized in various ways – according to Steinbuch, this could be done by hardware or software). To train
4-497: A Lernmatrix, values are specified on the corresponding characteristic and meaning lines (binary or real); 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,
#661338