Abstract
A simplified model of a stochastic neural network is considered, being a system of a large number of identical excitable FitzHugh-Nagumo oscillators coupled via the mean field. The possibility to control the global dynamics of this network is investigated. The control tool being probed is Pyrgas delayed feedback constructed
and applied through the mean field. It is shown that one can to destroy or diminish stochastic synchronization in a partially synchronized network by a weak delayed feedback under the appropriate choice of delay.
and applied through the mean field. It is shown that one can to destroy or diminish stochastic synchronization in a partially synchronized network by a weak delayed feedback under the appropriate choice of delay.
| Original language | English |
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| Publication status | Published - 1 Sep 2009 |
| Event | 4th International Scientific Conference on Physics and Control 2009 - Catania, Italy Duration: 1 Sep 2009 → 4 Sep 2009 |
Conference
| Conference | 4th International Scientific Conference on Physics and Control 2009 |
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| Abbreviated title | PhysCon 2009 |
| Country/Territory | Italy |
| City | Catania |
| Period | 1/09/09 → 4/09/09 |
Keywords
- Network
- Neuron
- Stochastic
- Delay
- Control