English

Methods for applying the Neural Engineering Framework to neuromorphic hardware

Neurons and Cognition 2017-08-29 v1 Artificial Intelligence Systems and Control Dynamical Systems

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).

Keywords

Cite

@article{arxiv.1708.08133,
  title  = {Methods for applying the Neural Engineering Framework to neuromorphic hardware},
  author = {Aaron R. Voelker and Chris Eliasmith},
  journal= {arXiv preprint arXiv:1708.08133},
  year   = {2017}
}

Comments

11 pages, no figures

R2 v1 2026-06-22T21:24:40.875Z