<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

Neural Flows in Hopfield Network Approach

Faculty of Exact Sciences, Department of Physics, University of Craiova, Str. A.I. Cuza, nr.13, 200585, Craiova, Dolj, Romania

Annals of West University of Timisoara - Physics

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"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...

Neural Flows in Hopfield Network Approach

Published Online: Oct 29, 2015

Page range: 1 - 9

Received: Feb 08, 2013

Accepted: Feb 27, 2013

DOI: https://doi.org/10.1515/awutp-2015-0101

Keywords
neural cell, nonlinear dynamics

© 2015

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Neural Flows in Hopfield Network Approach

Published Online: Oct 29, 2015

Page range: 1 - 9

Received: Feb 08, 2013

Accepted: Feb 27, 2013

DOI: https://doi.org/10.1515/awutp-2015-0101

Keywordsneural cell, nonlinear dynamics

© 2015

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Keywords
neural cell, nonlinear dynamics