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IJON
2000
76views more  IJON 2000»
13 years 4 months ago
Fast neural network simulations with population density methods
The complexity of neural networks of the brain makes studying these networks through computer simulation challenging. Conventional methods, where one models thousands of individua...
Duane Q. Nykamp, Daniel Tranchina
JCNS
2000
165views more  JCNS 2000»
13 years 4 months ago
A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientati
We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are ...
Duane Q. Nykamp, Daniel Tranchina
NECO
2007
108views more  NECO 2007»
13 years 4 months ago
Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories
We propose a Markov process model for spike-frequency adapting neural ensembles which synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneou...
Eilif Mueller, Lars Buesing, Johannes Schemmel, Ka...
BC
2006
105views more  BC 2006»
13 years 4 months ago
A stochastic population approach to the problem of stable recruitment hierarchies in spiking neural networks
Recruitment learning in hierarchies is an inherently unstable process (Valiant, 1994). This paper presents conditions on parameters for a feedforward network to ensure stable recru...
Cengiz Günay, Anthony S. Maida
CORR
2008
Springer
97views Education» more  CORR 2008»
13 years 4 months ago
Fast Density Codes for Image Data
Recently, a new method for encoding data sets in the form of "Density Codes" was proposed in the literature (Courrieu, 2006). This method allows to compare sets of points...
Pierre Courrieu