Methods for applying the Neural Engineering Framework to neuromorphic hardware

arXiv preprint arXiv:1708.08133, 2017

Aaron R. Voelker, Chris Eliasmith

Abstract

We review our current software tools and theoretical methods for applying the Neural Engineering Framework to state-of-the-art neuromorphic hardware. These methods can be used to implement linear and nonlinear dynamical systems that exploit axonal transmission time-delays, and to fully account for nonideal mixed-analog-digital synapses that exhibit higher-order dynamics with heterogeneous time-constants. This summarizes earlier versions of these methods that have been discussed in a more biological context (Voelker & Eliasmith, 2017) or regarding a specific neuromorphic architecture (Voelker et al., 2017).

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arXiv preprint arXiv:1708.08133

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