Delayed feedback control in stochastic excitable networks

Natalia Janson; Andrey Pototsky; Sandhya Patidar

Delayed feedback control in stochastic excitable networks

Natalia Janson, Andrey Pototsky, Sandhya Patidar

Research output: Contribution to conference › Paper › peer-review

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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.

Original language	English
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
Abbreviated title	PhysCon 2009
Country	Italy
City	Catania
Period	1/09/09 → 4/09/09

Keywords

Network
Neuron
Stochastic
Delay
Control

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title = "Delayed feedback control in stochastic excitable networks",

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 constructedand 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.",

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T1 - Delayed feedback control in stochastic excitable networks

AU - Janson, Natalia

AU - Pototsky, Andrey

AU - Patidar, Sandhya

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N2 - 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 constructedand 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.

AB - 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 constructedand 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.

KW - Network

KW - Neuron

KW - Stochastic

KW - Delay

KW - Control

M3 - Paper

T2 - 4th International Scientific Conference on Physics and Control 2009

Y2 - 1 September 2009 through 4 September 2009

ER -