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NCI
2004
198views Neural Networks» more  NCI 2004»
13 years 7 months ago
A "spiking" bidirectional associative memory for modeling intermodal priming
Starting from a modular artificial neural system modelling the integration of several perceptive stimuli, this article proposes a new implementation of the central module performi...
David Meunier, Hélène Paugam-Moisy
ICANN
2003
Springer
13 years 11 months ago
The Spike Response Model: A Framework to Predict Neuronal Spike Trains
We propose a simple method to map a generic threshold model, namely the Spike Response Model, to artificial data of neuronal activity using a minimal amount of a priori informatio...
Renaud Jolivet, Timothy J. Lewis, Wulfram Gerstner
FPL
2008
Springer
125views Hardware» more  FPL 2008»
13 years 7 months ago
Reconfigurable platforms and the challenges for large-scale implementations of spiking neural networks
FPGA devices have witnessed popularity in their use for the rapid prototyping of biological Spiking Neural Network (SNNs) applications, as they offer the key requirement of reconf...
Jim Harkin, Fearghal Morgan, Steve Hall, Piotr Dud...
FUIN
2008
103views more  FUIN 2008»
13 years 6 months ago
Implementing Sorting Networks with Spiking Neural P Systems
Spiking neural P systems simulate the behavior of neurons sending signals through axons. Recently, some applications concerning Boolean circuits and sorting algorithms have been pr...
Rodica Ceterchi, Alexandru Ioan Tomescu
IJCNN
2007
IEEE
14 years 17 days ago
Character Recognition using Spiking Neural Networks
— A spiking neural network model is used to identify characters in a character set. The network is a two layered structure consisting of integrate-and-fire and active dendrite n...
Ankur Gupta, Lyle N. Long