Asymptotic Description of Neural Networks with Correlated Synaptic Weights

Asymptotic Description of Neural Networks with Correlated Synaptic Weights

We study the asymptotic law of a network of interacting neurons when the number of neurons becomes infinite. Given a completely connected network of neurons in which the synaptic weights are Gaussian correlated random variables, we describe the asymptotic law of the network when the number of neuron...

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Bibliographic Details
Main Authors: Olivier Faugeras, James MacLaurin
Format: Article
Language:English
Published: MDPI AG 2015-07-01
Series:Entropy
Subjects:
large deviations
good rate function
stationary gaussian processes
stationary measures
spectral representations
neural networks
firing rate neurons
correlated synaptic weights
Online Access:http://www.mdpi.com/1099-4300/17/7/4701

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http://www.mdpi.com/1099-4300/17/7/4701

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