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Spiking neural network

Known as: SNN, Spiking neural networks 
Spiking neural networks (SNNs) fall into the third generation of neural network models, increasing the level of realism in a neural simulation. In… Expand
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Highly Cited
2015
Highly Cited
2015
Deep neural networks such as Convolutional Networks (ConvNets) and Deep Belief Networks (DBNs) represent the state-of-the-art for… Expand
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Highly Cited
2011
Highly Cited
2011
We propose a design methodology to exploit adaptive nanodevices (memristors), virtually immune to their variability. Memristors… Expand
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Highly Cited
2010
Highly Cited
2010
Spiking neural network simulators provide environments in which to implement and experiment with models of biological brain… Expand
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Highly Cited
2009
Highly Cited
2009
Memristor nanodevices have good properties for use as synapses to add dynamic learning to neuromorphic networks implemented in… Expand
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Highly Cited
2008
Highly Cited
2008
“Brian” is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and… Expand
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Highly Cited
2006
Highly Cited
2006
This paper describes an area-efficient mixed-signal implementation of synapse-based long term plasticity realized in a VLSI model… Expand
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Highly Cited
2003
Highly Cited
2003
Biological neurons use short and sudden increases in voltage to send information. These signals are more commonly known as action… Expand
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Highly Cited
2002
Highly Cited
2002
Abstract For a network of spiking neurons that encodes information in the timing of individual spike times, we derive a… Expand
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Highly Cited
1997
Highly Cited
1997
Abstract The computational power of formal models for networks of spiking neurons is compared with that of other neural network… Expand
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Highly Cited
1996
Highly Cited
1996
  • Wolfgang Maass
  • Electronic Colloquium on Computational Complexity
  • 1996
  • Corpus ID: 1753085
-The computational power of formal models for networks of spiking neurons is compared with that of other neural network models… Expand
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