Neural Flows in Hopfield Network Approach
In most of the applications involving neural networks, the main problem consists in finding an optimal procedure to reduce the real neuron to simpler models which still express the biological complexity but allow highlighting the main characteristics of the system. We effectively investigate a simpl...
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Series: | Annals of West University of Timisoara: Physics |
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Online Access: | https://doi.org/10.1515/awutp-2015-0101 |
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doaj-d2aec893c51c4a7890be6218fab655252021-09-06T19:40:24ZengSciendoAnnals of West University of Timisoara: Physics1224-97182013-12-015711910.1515/awutp-2015-0101Neural Flows in Hopfield Network ApproachIonescu Carmen0Panaitescu Emilian1Stoicescu Mihai2Faculty of Exact Sciences, Department of Physics, University of Craiova, Str. A.I. Cuza, nr.13, 200585, Craiova, Dolj, RomaniaFaculty of Exact Sciences, Department of Physics, University of Craiova, Str. A.I. Cuza, nr.13, 200585, Craiova, Dolj, RomaniaFaculty of Exact Sciences, Department of Physics, University of Craiova, Str. A.I. Cuza, nr.13, 200585, Craiova, Dolj, RomaniaIn most of the applications involving neural networks, the main problem consists in finding an optimal procedure to reduce the real neuron to simpler models which still express the biological complexity but allow highlighting the main characteristics of the system. We effectively investigate a simple reduction procedure which leads from complex models of Hodgkin-Huxley type to very convenient binary models of Hopfield type. The reduction will allow to describe the neuron interconnections in a quite large network and to obtain information concerning its symmetry and stability. Both cases, on homogeneous voltage across the membrane and inhomogeneous voltage along the axon will be tackled out. Few numerical simulations of the neural flow based on the cable-equation will be also presented.https://doi.org/10.1515/awutp-2015-0101neural cellnonlinear dynamics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ionescu Carmen Panaitescu Emilian Stoicescu Mihai |
spellingShingle |
Ionescu Carmen Panaitescu Emilian Stoicescu Mihai Neural Flows in Hopfield Network Approach Annals of West University of Timisoara: Physics neural cell nonlinear dynamics |
author_facet |
Ionescu Carmen Panaitescu Emilian Stoicescu Mihai |
author_sort |
Ionescu Carmen |
title |
Neural Flows in Hopfield Network Approach |
title_short |
Neural Flows in Hopfield Network Approach |
title_full |
Neural Flows in Hopfield Network Approach |
title_fullStr |
Neural Flows in Hopfield Network Approach |
title_full_unstemmed |
Neural Flows in Hopfield Network Approach |
title_sort |
neural flows in hopfield network approach |
publisher |
Sciendo |
series |
Annals of West University of Timisoara: Physics |
issn |
1224-9718 |
publishDate |
2013-12-01 |
description |
In most of the applications involving neural networks, the main problem consists in finding an optimal procedure to reduce the real neuron to simpler models which still express the biological complexity but allow highlighting the main characteristics of the system. We effectively investigate a simple reduction procedure which leads from complex models of Hodgkin-Huxley type to very convenient binary models of Hopfield type. The reduction will allow to describe the neuron interconnections in a quite large network and to obtain information concerning its symmetry and stability. Both cases, on homogeneous voltage across the membrane and inhomogeneous voltage along the axon will be tackled out. Few numerical simulations of the neural flow based on the cable-equation will be also presented. |
topic |
neural cell nonlinear dynamics |
url |
https://doi.org/10.1515/awutp-2015-0101 |
work_keys_str_mv |
AT ionescucarmen neuralflowsinhopfieldnetworkapproach AT panaitescuemilian neuralflowsinhopfieldnetworkapproach AT stoicescumihai neuralflowsinhopfieldnetworkapproach |
_version_ |
1717768625328226304 |