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IWANN
1997
Springer
14 years 1 days ago
Gray-Level Object Segmentation with a Network of FitzHugh-Nagumo Oscillators
Abstract. In this paper we adopt a temporal coding approach to neuronal modeling of the visual cortex, using oscillations. We propose a hierarchy of three processing modules corres...
Abderrahim Labbi, Ruggero Milanese, Holger Bosch
ICDM
2009
IEEE
156views Data Mining» more  ICDM 2009»
13 years 5 months ago
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging
We present an approach for learning models that obtain accurate classification of large scale data objects, collected in spatiotemporal domains. The model generation is structured ...
Igor Vainer, Sarit Kraus, Gal A. Kaminka, Hamutal ...
TNN
2010
147views Management» more  TNN 2010»
13 years 2 months ago
Theoretical Model for Mesoscopic-Level Scale-Free Self-Organization of Functional Brain Networks
In this paper we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph s...
J. Piersa, Filip Piekniewski, Tomasz Schreiber
IJCNN
2008
IEEE
14 years 2 months ago
Biologically realizable reward-modulated hebbian training for spiking neural networks
— Spiking neural networks have been shown capable of simulating sigmoidal artificial neural networks providing promising evidence that they too are universal function approximat...
Silvia Ferrari, Bhavesh Mehta, Gianluca Di Muro, A...
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