2 papers
q-bio.NC2016
Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System
Simon Friedmann, Johannes Schemmel, Andreas Gruebl +3
We present results from a new approach to learning and plasticity in neuromorphic hardware systems: to enable flexibility in implementable learning mechanisms while keeping high ef…
q-bio.NC2013
Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate
Simon Friedmann, Nicolas Frémaux, Johannes Schemmel +2
In this study, we propose and analyze in simulations a new, highly flexible method of implementing synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. T…