Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate

Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate

In this study, we propose and analyze in simulations a new, highly flexible method of imple-menting synaptic plasticity in a wafer-scale, accelerated neuromorphic hardware system. Thestudy focuses on globally modulated STDP, as a special use-case of this method. Flexibility isachieved by embedding a...

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Bibliographic Details
Main Authors: Simon eFriedmann, Nicolas eFrémaux, Johannes eSchemmel, Wulfram eGerstner, Karlheinz eMeier
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-09-01
Series:Frontiers in Neuroscience
Subjects:
reinforcement learning
neuromorphic hardware
spike-timing dependent plasticity
wafer-scale integration
large-scale spiking neural net- works
hardware constraints analysis
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2013.00160/full

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