Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity
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Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations.Characterization and compensation of network-level anomalies in mixed-signal neuromorphic modeling platforms.Six networks on a universal neuromorphic computing substrate.Binary Associative Memories as a Benchmark for Spiking Neuromorphic Hardware.Is a 4-bit synaptic weight resolution enough? - constraints on enabling spike-timing dependent plasticity in neuromorphic hardware.Effect of Heterogeneity on Decorrelation Mechanisms in Spiking Neural Networks: A Neuromorphic-Hardware StudyProbabilistic Inference in Neural NetworksNeuromorphic computing using non-volatile memory
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P2860
Compensating Inhomogeneities of Neuromorphic VLSI Devices Via Short-Term Synaptic Plasticity
description
2010 nî lūn-bûn
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2010年の論文
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2010年学术文章
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name
Compensating Inhomogeneities o ...... Short-Term Synaptic Plasticity
@en
Compensating Inhomogeneities o ...... hort-Term Synaptic Plasticity.
@nl
type
label
Compensating Inhomogeneities o ...... Short-Term Synaptic Plasticity
@en
Compensating Inhomogeneities o ...... hort-Term Synaptic Plasticity.
@nl
prefLabel
Compensating Inhomogeneities o ...... Short-Term Synaptic Plasticity
@en
Compensating Inhomogeneities o ...... hort-Term Synaptic Plasticity.
@nl
P2093
P2860
P50
P356
P1476
Compensating Inhomogeneities o ...... Short-Term Synaptic Plasticity
@en
P2093
Daniel Brüderle
Johannes Bill
Karlheinz Meier
Klaus Schuch
P2860
P356
10.3389/FNCOM.2010.00129
P577
2010-10-08T00:00:00Z