Physical mapping of spiking neural networks models on a bio-inspired scalable architecture

Abstract

The paper deals with the physical implementation of biologically plausible spiking neural network models onto a hardware architecture with bio-inspired capabilities. After presenting the model, the work will illustrate the major steps taken in order to provide a compact and efficient digital hardware implementation of the model. Special emphasis will be given to the scalability features of the architecture, that will permit the implementation of large-scale networks. The paper will conclude with details about the physical mapping of the model, as well as with experimental results obtained when applying dynamic input stimuli to the implemented network. © Springer-Verlag Berlin Heidelberg 2006.