A flexible hardware architecture for online Hebbian learning in the sender-oriented PCNN-neurocomputer Spike 128 K

In this paper we describe a hardware architecture that provides online Hebbian learning for PCNNs according to different learning rules. This architecture is an extension of the Spike 128 K-system which is shortly introduced, focusing the sender-oriented structure of the entire system. The algorithms derived for three well proved Hebbian learning-rules are compatible with this sender-oriented structure. The introduced architecture integrates processing of these learning-rules very efficiently into the Spike 128 K-system