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).
- Pub Date:
- August 2017
- Quantitative Biology - Neurons and Cognition;
- Computer Science - Artificial Intelligence;
- Computer Science - Systems and Control;
- Mathematics - Dynamical Systems
- 11 pages, no figures