Add to ORKGA framework for studying the behavior of a classically frustrated signed network in the process of random rewiring is developed. We describe jump probabilities for change in frustration and formulate a theoretical estimate in terms of the master equation. Stationary thermodynamic distribution and moments are derived from the master equation and compared to numerical simulations. Furthermore, an exact solution of the probability distribution is provided through suitable mapping of rewiring dynamic to birth and death processes with quadratic asymptotically symmetric transition rates.Comment: 12 pages, 10 figure
This article presents an approximate analytical solution for the connectivity of a network model wit...
Previous explanations of computations performed by recurrent networks have focused on symmetrically ...
This article is a preprint of a paper that is currently under review with Physical Review E.We study...
This is the peer reviewed version of the following article: A. Inglis, L. Cruz, D.L. Roe, H.E. Stanl...
A problem central to many scientific and engineering disciplines is how to deal with noisy dynamic p...
Background: For large-scale biological networks represented as signed graphs, the index of frustrati...
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe...
We look at the evolution through rewiring of the degree distribution of a network so the number edge...
A signed network is a network in which each link is associated with a positive or negative sign. Mod...
[Background]: Networks are popular and powerful tools to describe and model biological processes. Ma...
<div><p>The role intrinsic statistical fluctuations play in creating avalanches – patterns of comple...
We propose a simple model that captures the salient properties of distribution networks, and study t...
The computational abilities of recurrent networks of neurons with a linear activation function above...
© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attributio...
The remarkable properties of information-processing by biological and artificial neuronal networks a...
This article presents an approximate analytical solution for the connectivity of a network model wit...
Previous explanations of computations performed by recurrent networks have focused on symmetrically ...
This article is a preprint of a paper that is currently under review with Physical Review E.We study...
This is the peer reviewed version of the following article: A. Inglis, L. Cruz, D.L. Roe, H.E. Stanl...
A problem central to many scientific and engineering disciplines is how to deal with noisy dynamic p...
Background: For large-scale biological networks represented as signed graphs, the index of frustrati...
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel UniversityThe...
We look at the evolution through rewiring of the degree distribution of a network so the number edge...
A signed network is a network in which each link is associated with a positive or negative sign. Mod...
[Background]: Networks are popular and powerful tools to describe and model biological processes. Ma...
<div><p>The role intrinsic statistical fluctuations play in creating avalanches – patterns of comple...
We propose a simple model that captures the salient properties of distribution networks, and study t...
The computational abilities of recurrent networks of neurons with a linear activation function above...
© The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attributio...
The remarkable properties of information-processing by biological and artificial neuronal networks a...
This article presents an approximate analytical solution for the connectivity of a network model wit...
Previous explanations of computations performed by recurrent networks have focused on symmetrically ...
This article is a preprint of a paper that is currently under review with Physical Review E.We study...