45 search results - page 5 / 9 » Error-backpropagation in temporally encoded networks of spik... |
ICANN
2010
Springer
13 years 8 months ago
2010
Springer
Abstract. Spiking Neuron Networks (SNNs) overcome the computational power of neural networks made of thresholds or sigmoidal units. Indeed, SNNs add a new dimension, the temporal a...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Problem statement: This paper examines Artificial Spiking Neural Network (ASNN) which inter-connects group of artificial neurons that uses a mathematical model with the aid of blo...
ISCAS
2003
IEEE
14 years 22 days ago
2003
IEEE
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
ESANN
2007
13 years 9 months ago
2007
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...
ICDM
2009
IEEE
14 years 2 months ago
2009
IEEE
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...