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» Phenomenological models of synaptic plasticity based on spik...
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ESANN
2007
13 years 9 months ago
A supervised learning approach based on STDP and polychronization in spiking neuron networks
We propose a network model of spiking neurons, without preimposed topology and driven by STDP (Spike-Time-Dependent Plasticity), a temporal Hebbian unsupervised learning mode, biol...
Hélène Paugam-Moisy, Régis Ma...
NIPS
2003
13 years 9 months ago
Analytical Solution of Spike-timing Dependent Plasticity Based on Synaptic Biophysics
Spike timing plasticity (STDP) is a special form of synaptic plasticity where the relative timing of post- and presynaptic activity determines the change of the synaptic weight. O...
Bernd Porr, Ausra Saudargiene, Florentin Wörg...
SYNASC
2005
IEEE
97views Algorithms» more  SYNASC 2005»
14 years 1 months ago
A Reinforcement Learning Algorithm for Spiking Neural Networks
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
Razvan V. Florian
CONNECTION
2006
172views more  CONNECTION 2006»
13 years 7 months ago
Temporal sequence detection with spiking neurons: towards recognizing robot language instructions
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Christo Panchev, Stefan Wermter