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.
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Moreno, J.M., Iglesias, J., Eriksson, J.L., Villa, A.E.P. (2006). Physical Mapping of Spiking Neural Networks Models on a Bio-inspired Scalable Architecture. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds) Artificial Neural Networks – ICANN 2006. ICANN 2006. Lecture Notes in Computer Science, vol 4131. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11840817_97
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DOI: https://doi.org/10.1007/11840817_97
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38625-4
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