Compensating inhomogeneities of neuromorphic VLSI devices via short-term synaptic plasticity

Compensating inhomogeneities of neuromorphic VLSI devices via short-term synaptic plasticity

Recent developments in neuromorphic hardware engineering make mixed-signal VLSI neural network models promising candidates for neuroscientific research tools and massively parallel computing devices, especially for tasks which exhaust the computing power of software simulations. Still, lik...

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Bibliographic Details
Main Authors: Johannes Bill, Klaus Schuch, Daniel Brüderle, Johannes Schemmel, Wolfgang Maass, Karlheinz Meier
Format: Article
Language:English
Published: Frontiers Media S.A. 2010-10-01
Series:Frontiers in Computational Neuroscience
Subjects:
robustness
Self-regulation
neuromorphic hardware
Parallel Computing
Leaky Integrate-and-Fire Neuron
PCSIM
Online Access:http://journal.frontiersin.org/Journal/10.3389/fncom.2010.00129/full

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