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» Spike-timing-dependent plasticity in small-world networks
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NIPS
2003
13 years 6 months ago
Synchrony Detection by Analogue VLSI Neurons with Bimodal STDP Synapses
We present test results from spike-timing correlation learning experiments carried out with silicon neurons with STDP (Spike Timing Dependent Plasticity) synapses. The weight chan...
Adria Bofill-i-Petit, Alan F. Murray
ISCAS
2011
IEEE
278views Hardware» more  ISCAS 2011»
12 years 9 months ago
A programmable axonal propagation delay circuit for time-delay spiking neural networks
— we present an implementation of a programmable axonal propagation delay circuit which uses one first-order logdomain low-pass filter. Delays may be programmed in the 550ms rang...
Runchun Wang, Craig T. Jin, Alistair McEwan, Andr&...
IJON
2007
93views more  IJON 2007»
13 years 5 months ago
How much can we trust neural simulation strategies?
Despite a steady improvement of computational hardware, results of numerical simulation are still tightly bound to the simulation tool and strategy used, and may substantially var...
Michelle Rudolph, Alain Destexhe
IWANN
2005
Springer
13 years 10 months ago
Real-Time Spiking Neural Network: An Adaptive Cerebellar Model
Abstract. A spiking neural network modeling the cerebellum is presented. The model, consisting of more than 2000 conductance-based neurons and more than 50 000 synapses, runs in re...
Christian Boucheny, Richard R. Carrillo, Eduardo R...
NIPS
2004
13 years 6 months ago
Maximising Sensitivity in a Spiking Network
We use unsupervised probabilistic machine learning ideas to try to explain the kinds of learning observed in real neurons, the goal being to connect abstract principles of self-or...
Anthony J. Bell, Lucas C. Parra